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From The Desk of HOD Keeping with the motto of Acquire Knowledge and Grow, under patronage of our Director, Dr. R.K. Agarwal, department has published the Vol. 5, No. 2 a half-yearly Journal. The aim of publishing Journal of Computer Application (JCA) is to inculcate habit of writing and reading a technical paper among faculty and students. Topics and contents have been selected to educate our students on current state of the art technology of common applications in simplistic manner without going through the mathematical details. Length of topics have deliberately been kept very short to accommodate most of the writers, and keep the interest of readers as well. My sincere appreciation to all writers specially to students of MCA department. Enjoy the reading and kindly offer your valuable suggestion for improvement in our subsequent issues. Looking ahead for your support. Prof. S. L. Kapoor
CONTENTS
S. No. TITLE Page No.
1 Security in ADHOC Sensor Networks 5-10
Dr. Lalit Kishore Arora
2 Cleaning Online World 11-13
Saroj Bala
3 Current status of Machine Translation in India 14-16
Pooja Arora
4 Evolution of edge Technology in mobile communications for gsm - a review article 17-21
Sanjeev K. Prasad
5 Energy Efficient Skewed Tree based indexing Scheme for Skewed 22-26
Access Patterns in Wireless Environment
Mani Dwivedi
6 A Survey on Parallel Genetic Algorithms 27-29
Ruchi Gupta
7 StarUML: An open-source UML modeling tool 30-32
Aditya Pratap Singh
8 Electronic Paper Display Technologies 33-35
Arpna Saxena
9 5G Technology of Mobile Communication: A Survey 36-39
Anjali Singh
10 Usage of Domain Testing For Early Prediction of Testability of Software 40-43
Pratima Singh
11 SQUARE – An Electronic Payment System 44-45
Snehlata Kaul
12 Introduction to Programming with RAPTOR 46-48
Dr. B.K. Sharma
Journal of Computer Application, Volume 5, No. 2, July-December 2014
Ajay Kumar Garg Engineering College, Ghaziabad
4
SECURITY IN ADHOC SENSOR NETWORKS
Dr. Lalit Kishore Arora
Assistant Professor, MCA Department, AKGEC, GZB
Abstract— An adhoc network is a group of wireless mobile describe several new attacks on ad hoc network routing
computers (or nodes), in which individual nodes cooperate by protocols. Second, we present the design and performance
forwarding packets for each other to allow nodes to communicate evaluation of a new on-demand secure ad hoc network
beyond direct wireless transmission range. Prior research in routing protocol, called Ariadne, that withstands node
ad hoc networking has generally studied the routing problem
compromise and relies only on highly efficient symmetric
in a non-adversarial setting, assuming a trusted environment.
This paper presents attacks against routing in ad hoc networks, cryptography. Relative to previous work in securing ad hoc
and the design and performance evaluation of a new secure on- network routing protocols, Ariadne is more secure, more
demand ad hoc network routing protocol, called Ariadne. efficient, or more general (e.g., Ariadne does not require
Ariadne prevents attackers or compromised nodes from trusted hardware and does not require powerful
tampering with uncompromised routes consisting of processors). Ariadne can authenticate routing messages
uncompromised nodes, and also prevents many types of Denial- using one of three schemes: shared secret keys between
of-Service attacks. In addition, Ariadne is efficient, using only all pairs of nodes, shared secret keys between
highly efficient symmetric cryptographic primitives. communicating nodes combined with broadcast
authentication, or digital signatures. We primarily discuss
Keywords: Adhoc Networks, Ariadne, DoS, Symmetric
cryptographic, OnDemand Routing Protocol here the use of Ariadne with TESLA [10,11], an efficient
broadcast authentication scheme that requires loose time
synchronization. Using pair wise shared keys avoids the
I. INTRODUCTION need for synchronization, but at the cost of higher key
An ad hoc network is a group of wireless mobile setup overhead; broadcast authentication such as TESLA
computers (or nodes), in which nodes cooperate by also allows some additional protocol optimizations.
forwarding packets for each other to allow them to
communicate beyond direct wireless transmission range. So II. DYNAMIC SOURCE ROUTING
far, researchers in ad hoc networking have generally We base the design of our secure on-demand ad hoc
studied the routing problem in a non-adversarial network network routing protocol, Ariadne, on the basic operation
setting, assuming a trusted environment; relatively little of the Dynamic Source Routing protocol (DSR) [15], since
research has been done in a more realistic setting in which DSR operates entirely on- demand and has been well
an adversary may attempt to disrupt the communication. studied through both simulation and real test bed
We focus here on on-demand (or reactive) routing implementation [8,14,]. Unlike periodic protocols (e.g.,
protocols for ad hoc networks, in which a node attempts [4,9,5]), which exchange routing information between nodes
to discover a route to some destination only when it has a periodically in an attempt to always maintain routes to all
packet to send to that destination. On-demand routing destinations, on-demand protocols exchange routing
protocols have been demonstrated to perform better with information only when a new route is needed to deliver a
significantly lower overheads than periodic (or proactive) packet to some destination. On-demand approaches to
routing protocols in many situations [8,14,12], since the routing in ad hoc networks often have lower overhead than
protocol is able to react quickly to the many changes that periodic protocols, since they transmit routing information
may occur in node connectivity, yet is able to reduce (or only in response to actual packets to be sent or in
eliminate) routing overhead in periods or areas of the response to topology changes affecting routes actively in
network in which changes are less frequent. In this paper, use. In a secure routing protocol, reduced overhead has
we make two contributions to the area of secure routing the added benefit of reducing the number of routing
protocols for ad hoc networks. First, we give a model for packets that need to be authenticated, thereby reducing
the types of attacks possible in such a system, and we the computational overhead needed for security.
5
Journal of Computer Application, Volume 5, No. 2, July-December 2014
Ajay Kumar Garg Engineering College, Ghaziabad
III. TESLA Most routing disruption attacks are caused by malicious
In this paper, we describe Ariadne primarily using the injection or altering of routing data. To prevent these
TESLA [10,11] broadcast authentication protocol for attacks, each node that interprets routing information must
authenticating routing messages, since TESLA is efficient verify the origin and integrity of that data; that is, it must
and adds only a single Message Authentication Code authenticate the data. Ideally, the initiator of the Route
(MAC) to a message for broadcast authentication. Adding Discovery can verify the origin of each individual data field
a MAC (computed with a shared key) to a message can in the ROUTE REPLY.
provide secure authentication in point-to-point
communication; for broadcast communication, however, We need an authentication mechanism with low
multiple receivers need to know the MAC key for computation and communication overhead. An inefficient
verification, which would also allow any receiver to forge authentication mechanism could be exploited by an attacker
packets and impersonate the sender. Secure broadcast to perform a Denial-of-Service (DoS) attack by flooding
authentication thus requires an asymmetric primitive, such nodes with malicious messages, overwhelming them with
that the sender can generate valid authentication the cost of verifying authentication. Thus, for point-to-
information, but the receivers can only verify the point authentication of a message, we use a message
authentication information. TESLA differs from traditional authentication code (MAC) (e.g., HMAC [3]) and a shared
asymmetric protocols such as RSA [7] in that TESLA key between the two parties. However, setting up the
achieves this asymmetry from clock synchronization and shared keys between the initiator and all the nodes on the
delayed key disclosure, rather than from computationally path to the target may be expensive. We thus also propose
expensive one-way trapdoor functions. To use TESLA for using the TESLA broadcast authentication protocol for
authentication, each sender chooses a random initial key authentication of nodes on the routing path. However, we
KN and generates a one-way key chain by repeatedly also discuss MAC authentication with pairwise shared
computing a one-way hash function H on this starting keys, for networks capable of inexpensive key setup, and
value: KN-1 = H[KN], KN-2 = H[KN-1], . . . . In general, Ki we discuss digital signatures for authentication, for
= H[Ki+1] = HN-i [KN]. To compute any previous key Kj networks with extremely powerful nodes.
from a key Ki, j < i, a node uses the equation Kj = Hi-j [Ki
]. To authenticate any received value on the one-way As a general design principle, a node trusts only itself for
chain, a node applies this equation to the received value to acquiring information about which nodes in the network
determine if the computed value matches a previous are malicious. This approach helps avoid blackmail attacks,
known authentic key on the chain. Coppersmith and where an attacker constructs information to make a
Jakobsson present efficient mechanisms for storing and legitimate node appear malicious. In our design, we assume
generating values of hash chains [13]. that a sender trusts the destination with which it
communicates, for authenticating nodes on the path
IV. ARIADNE between them. This assumption is straightforward, as the
destination node can control all communication with the
A. Design goals sender anyway. However, the destination node can
We aim for resilience against Active-1-x and Active-y-x potentially blackmail nodes on the path to the sender. The
attackers. Ideally, the probability that the routing protocol sender thus needs to keep a separate blacklist for each
de-livers messages degrades gracefully when nodes fail or destination.
are compromised. Our goal is to design simple and
efficient mechanisms achieving high attack robustness. In general, ad hoc network routing protocols do not need
These mechanisms should be sufficiently general to allow secrecy or confidentiality. These properties are required to
application to a wide range of routing protocols. Defending achieve privacy or anonymity for the sender of messages.
against an Active-0-x attacker is relatively easy. A network- Even in the Internet, it is challenging to achieve sender
wide shared secret key limits the attacker to replaying anonymity, and this area is still the subject of active
messages. Thus the main attacks remaining are the research. Our protocol does not prevent an attacker from
wormhole and rushing attacks Packet leashes [25] can injecting data packets.
prevent both attacks because they prevent an Active-0-x
attacker from retransmitting packets. These approaches also B. Basic Ariadne Route Discovery
trivially secure a network routing protocol that uses In this section, we describe the basic operation of Route
tamper proof hardware, since the strongest attacker in such Discovery in Ariadne. We first overview the features of the
an environment is an Active-0-x attacker, assuming all protocol in three stages: we present a mechanism that
routing and security functionality (including packet enables the target of a Route Discovery to verify the
leashes) is implemented in the secure hardware. authenticity of the ROUTE REQUEST; we then present
6Security in ADHOC Sensor Networks
three alternative mechanisms for authenticating data in Finally, no key list is required in the REPLY. Ariadne Route
ROUTE REQUESTs and ROUTE REPLYs; and we present Discovery using MACs is the most efficient of the three
an efficient per-hop hashing technique to verify that no alternative authentication mechanisms, but it requires pair
node is missing from the node list in the REQUEST. After wise shared keys between all nodes. When Ariadne is
this overview, we present in detail the operation of Route used in this way, the MAC list in the ROUTE REQUEST is
Discovery in Ariadne when TESLA is used as the computed using a key shared between the target and the
authentication mechanism. In the following discussion, we current node, rather than using the TESLA key of the
assume that some initiator node S performs a Route current node. The MACs are verified at the target and are
Discovery for a target node D, and that they share the not returned in the ROUTE REPLY. As a result, the target
secret keys KSD and KDS, respectively, for message MAC is not computed over the MAC list in the REQUEST.
authentication in each direction. Target authenticates In addition, no key list is required in the REPLY.
ROUTE REQUESTs. To convince the target of the
legitimacy of each field in a ROUTE REQUEST, the initiator Per-hop hashing. Authentication of data in routing
simply includes in the REQUEST a MAC computed with messages is not sufficient, as an attacker could remove a
key KSD over unique data, for example a timestamp. The node from the node list in a ROUTE REQUEST. We use
target can easily verify the authenticity and freshness of one-way hash functions to verify that no hop was omitted,
the ROUTE REQUEST using the shared key KSD. and we call this approach per-hop hashing. To change or
remove a previous hop, an attacker must either hear a
Three techniques for route data authentication. ROUTE REQUEST without that node listed, or it must be
In a Route Discovery, the initiator wants to authenticate able to invert the one way hash function.
each individual node in the node list of the ROUTE REPLY.
A secondary requirement is that the target can authenticate Ariadne Route Discovery with TESLA. We now describe
each node in the node list of the ROUTE REQUEST, so in detail the version of Ariadne Route Discovery using
that it will return a ROUTE REPLY only along paths that TESLA broadcast authentication. We assume that every
contain only legitimate nodes. In this section, we present end-to-end communicating source–destination pair of nodes
three alternative techniques to achieve node list A and B share the MAC keys KAB and KBA. We also
authentication: the TESLA protocol, digital signatures, and assume that every node has a TESLA one-way key chain,
standard MACs. and that all nodes know an authentic key of the TESLA
one-way key chain of each other node. Route Discovery
When Ariadne Route Discovery is used with TESLA, each has two stages: the initiator floods the network with a
hop authenticates the new information in the REQUEST. ROUTE REQUEST, and the target returns a ROUTE REPLY.
The target buffers and does not send the REPLY until To secure the ROUTE REQUEST packet, Ariadne provides
intermediate nodes can release the corresponding TESLA the following properties: (1) the target node can
keys. The TESLA security condition is verified at the authenticate the initiator (using a MAC with a key shared
target, and the target includes a MAC in the REPLY to between the initiator and the target); (2) the initiator can
certify that the security condition was met. TESLA requires authenticate each entry of the path in the ROUTE REPLY
each packet sender to choose a a pessimistic upper bound (each intermediate node appends a MAC with its TESLA
t on the end-to-end network delay between nodes for key); and (3) no intermediate node can remove a previous
sending this packet, in order to select the TESLA key it node in the node list in the REQUEST or REPLY (a one-
will use to authenticate it. Choices of t do not affect the way function prevents a compromised node from removing
security of the protocol, although values that are too small a node from the node list). A ROUTE REQUEST packet in
may cause the Route Discovery to fail. Ariadne can Ariadne contains eight fields: _ROUTE REQUEST, initiator,
choose t adaptively, by increasing t when a Discovery target, id, time interval, hash chain, node list, MAC list_.
fails. In addition, the target of the Discovery could provide The initiator and target are set to the address of the
feedback in the ROUTE REPLY when t was chosen too initiator and target nodes, respectively. As in DSR, the
large. If Ariadne Route Discovery is used with digital initiator sets the id to an identifier that it has not recently
signatures, instead, the authentication differs in that no used in initiating a Route Discovery. The time interval is
Route Discovery chain element is required. In addition, the the TESLA time interval at the pessimistic expected arrival
MAC list in the ROUTE REQUEST becomes a signature time of the REQUEST at the target, accounting for clock
list, where the data used to compute the MAC is instead skew; specifically, given τ, a pessimistic transit time, the
used to compute a signature. Rather than computing the time interval could be set to any time interval for which the
target MAC using a Message Authentication Code, a key is not released within the next τ + 2_ time. The
signature is used. initiator of the REQUEST then initializes the hash chain to
7Journal of Computer Application, Volume 5, No. 2, July-December 2014
Ajay Kumar Garg Engineering College, Ghaziabad
MACKSD (initiator, target, id, time interval) and the node C. Thwarting the effects of routing misbehavior
list and MAC list to empty lists. When any node A The protocol described so far is vulnerable to an Active-1-
receives a ROUTE REQUEST for which it is not the target, 1 attacker that happens to be along the discovered route.
the node checks its local table of _initiator, id_values In particular, we have not presented a means of
from recent REQUESTs it has received, to determine if it determining whether intermediate nodes are, in fact,
has already seen a REQUEST from this same Route forwarding packets that they have been requested to
Discovery. forward. Watchdog and pathrater [15] attempt to solve this
problem by identifying the attacking nodes and avoiding
If it has, the node discards the packet, as in DSR. The them in the routes used.
node also checks whether the time interval in the
REQUEST is valid: that time interval must not be too far in Instead, we choose routes based on their prior performance
the future, and the key corresponding to it must not have in packet delivery. Introducing mechanisms that penalize
been disclosed yet. If the time interval is not valid, the specific nodes for routing misbehavior (such as is done in
node discards the packet. Otherwise, the node modifies the watchdog and pathrater) is subject to a blackmail attack,
REQUEST by appending its own address, A, to the node where a sufficient number of attackers may be able to
list in the REQUEST, replacing the hash chain field with penalize a well-behaved node. Our scheme relies on
H[A, hash chain], and appending a MAC of the entire feedback about which packets were successfully delivered.
REQUEST to the MAC list. The node uses the TESLA key The feedback can be received either through an extra end-
KAi to compute the MAC, where i is the index for the time to-end network layer message, or by exploiting properties
interval specified in the REQUEST. Finally, the node of transport layers, such as TCP with SACK [16]; this
rebroadcasts the modified REQUEST, as in DSR. When the feedback approach is somewhat similar that used in IPv6
target node receives the ROUTE REQUEST, it checks the for Neighbor Unreachability Detection [17]. Stronger
validity of the REQUEST by determining that the keys properties are obtained when the routing protocol sends
from the time interval specified have not been disclosed such feedback packets along a route equal to the reversed
yet, and that the hash chain field is equal to H_ηn,H_ηn- route of the triggering packet; otherwise, a malicious node
1,H_. . . ,H_ η 1,MACKSD (initiator, target, id, time along one route may drop the acknowledgment for a
interval)_ . . .___,where ηi is the node address at position packet transmitted along a functioning route. A node with
i of the node list in the REQUEST, and where n is the multiple routes to a single destination can assign a fraction
number of nodes in the node list. If the target node of packets that it originates to be sent along each route.
determines that the REQUEST is valid, it returns a ROUTE When a substantially smaller fraction of packets sent along
REPLY to the initiator, containing eight fields: _ROUTE any particular route are successfully delivered, the node
REPLY, target, initiator, time interval, node list, MAC list, can begin sending a smaller fraction of its overall packets
target MAC, key list_. The target, initiator, time interval, to that destination along that route. However, if the
node list, and fraction of packets chosen to be sent along a route that
appears to be misbehaving were to reach zero, a short-lived
MAC list fields are set to the corresponding values from jamming attack that is now over could still prevent the
the ROUTE REQUEST, the target MAC is set to a MAC future use of that route.
computed on the preceding fields in the REPLY with the
key KDS, and the key list is initialized to the empty list. To avoid this possible DoS attack, we choose the fraction
The ROUTE REPLY is then returned to the initiator of the of packets sent along such a route to be some small but
REQUEST along the source route obtained by reversing the nonzero amount, to allow the occasional monitoring of the
sequence of hops in the node list of the REQUEST. A route. A packet sent for this purpose can be a normal data
node forwarding a ROUTE REPLY waits until it is able to packet, or, if all packets are secured using end-to-end
disclose its key from the time interval specified; it then encryption, a padded “probe” packet can be used. Because
appends its key from that time interval to the key list field DSR often returns multiple ROUTE REPLY packets in
in the REPLY and forwards the packet according to the response to a Route Discovery, the presence of multiple
source route indicated in the packet. Waiting delays the routes to some destination in a node’s Route Cache is
return of the ROUTE REPLY but does not consume extra quite common. T sirigos and Haas [2] also discuss the use
computational power. When the initiator receives a ROUTE of multiple routes for increasing reliability, although they
REPLY, it verifies that each key in the key list is valid, do not discuss this technique with respect to secure
that the target MAC is valid, and that each MAC in the routing protocols. Malicious nodes can also be avoided
MAC list is valid. If all of these tests succeed, the node during Route Discovery. Each ROUTE REQUEST can
accepts the ROUTE REPLY; otherwise, it discards it. include a list of nodes to avoid, and the MAC that forms
8Security in ADHOC Sensor Networks
the initial hash chain element (h0) is then also computed given the disclosed (or known) symmetric keys.
over that list of nodes. Malicious nodes cannot add or
remove nodes from this list without being detected by the V. ARIADNE EVALUATION.
target. Choosing which nodes to avoid in this way is
beyond the scope of this paper. Security analysis
Intuitively, Ariadne Route Discovery is successful when at
D.Thwarting malicious route request floods least one of the REPLYs returned by the target is a
The chain can then be used to sign any set of immutable working route. Since the target of a Route Discovery
fields in the initial ROUTE REQUEST, and the signature returns a route for each of its neighbors, if the first
distributed with the REQUEST. In our design, the only REQUEST from a particular Discovery to reach any
immutable field is the target address, since the identifier is neighbor of the target has passed through no malicious
the chain element used for the current Route Discovery, nodes, that Discovery will succeed. To more formally
and the time interval can also be derived from that chain characterize the security offered by Ariadne, we define a
element. As a result, the one-time signature scheme needs minimum broadcast latency path between a source and a
to sign very few bits, and steps in the Route Discovery destination to be any path that forwards a Route
chain can be very inexpensive. For example, in a network Discovery most quickly from the source to the destination.
with 50 nodes, it suffices to represent 49 possible targets We call a route that only consists of uncompromised
(since the initiator is never the target). If the Merkle– nodes an uncompromised route. Ariadne prevents
Winternitz construction is used with two signature chains compromised nodes from disturbing uncompromised routes.
of length 7 and a checksum chain of length 13, each In particular, Ariadne provides two properties assuming
ROUTE REQUEST is just 20 bytes longer, and one step in reliable broadcast:
the hash chain costs just 27 hash operations. If each node
is permitted to initiate one Route Discovery per second, z If there exists an uncompromised neighbor of a
the amortized cost of using Merkle–Winternitz chains in destination such that the minimum latency path
this network is just 1350 hash operations per second. between the initiator of the Discovery and that
neighbor is uncompromised, then an uncompromised
E. Optimizations for Ariadne route from the initiator to the target will be returned
Caching improvements. When Ariadne is used with in a ROUTE REPLY.
broadcast authentication such as TESLA, additional route z If at least one REPLY returned as a result of the first
caching is possible. In the basic Route Discovery property represents a shortest route from the initiator
mechanism is only the initiator of the Discovery can use to the target, Ariadne may route packets along one
the route in the ROUTE REPLY, since the target MAC such uncompromised route.
field of the REPLY can only be verified by the initiator.
However, if the appropriate data is also broadcast VI. CONCLUSIONS
authenticated, any node along a path returned in a REPLY This paper has presented the design and evaluation of
can use that route to reach the target. For example, if Ariadne, a new secure ad hoc network routing protocol.
TESLA is used as the broadcast authentication protocol, a Ariadne provides security against one compromised node
target authenticator is placed the packet in addition to the and arbitrary active attackers, and relies only on efficient
target MAC, and is computed using a TESLA key that is symmetric cryptographic operations. Ariadne operates on-
not expected to be disclosed until _ after the last REPLY demand, dynamically discovering routes between nodes
reaches the initiator (where_ is the maximum time only as needed; the design is based on the basic opera-
difference between two nodes). That TESLA key is then tion of the DSR protocol. Rather than generously applying
disclosed, after appropriate delay, by sending it to the cryptography to an existing protocol to achieve security,
initiator along each path traversed by a REPLY. Reduced however, we carefully re-designed each protocol message
overhead. When Ariadne is used with symmetric and its processing. The security mechanisms we designed
authentication (such as TESLA or pairwise shared keys), are highly efficient and general, so that they should be
some fields can be calculated by the receiver rather than applicable to securing a wide variety of routing protocols.
included in the packet In particular, the MAC list in both
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SIGCOMM’94 Conference on Communications degree in computer science from
Architectures, Protocols and Applications (August Gurukul Kangri Vishwa Vidyalaya, Haridwar, UK in 2013.
1994) pp. 234–244. His research interest includes Interconnection Networks, Wireless
[10]. Perrig, R. Canetti, D. Song and J.D. Tygar, Efficient Networks and Sensor Networks. He published several research
papers in National and International journals. He has strong
and secure source authentication for multicast, in:
programming skills in object oriented programming languages. He
Proceedings of the Network and Distributed System also authored several books on object oriented programming lan-
Security Symposium, NDSS’01 (February 2001) pp. guages, such as C#.NET, JAVA, and C++. He has contributed
35– 46. several times to curriculum design and development in well
[11]. Perrig, R. Canetti, J.D. Tygar and D. Song, Efficient known universities in India and abroad. Besides authoring text-
authentication and signing of multicast streams over books, he enjoys participating in conferences and seminars about
lossy channels, in: Proceedings of the IEEE Sympo- technology and other socially relevant topics.
sium on Security and Privacy (May 2000) pp. 56– 73.
[12]. C.E. Perkins and E.M. Royer, Ad-hoc on-demand dis-
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Workshop on Mobile Computing Systems and Ap-
plications (WMCSA’99) (February 1999) pp. 90–100.
10CLEANING ONLINE WORLD
Saroj Bala
Assistant Professor, MCA Department, AKGEC, GZB
saroj_kkr@rediffmail.com
Abstract— These days global warming and energy efficiency real world, shifting investment from legacy coal, gas and
have been put on top of the list of the world global challenges. nuclear power plants to renewable energy technologies.
So, same for Cloud computing, a big challenge is to be able to
reduce its carbon and energy footprints, while keeping up with In US states like North Carolina, Nevada and Iowa, these
the high growth rate of storage, server and communication
companies’ commitments to clean energy are resulting in
infrastructures. In this article, we presented some findings of
reports on the approaches taken by different companies towards large amounts of wind and solar power displacing coal, gas
green clicks. and nuclear plants or preventing them from being built, to
the tangible benefit of the global climate and communities
living in those states.
1. INTRODUCTION
For the estimated 2.5 billion people around the world who The environmental rationale for technology companies to
are connected to the internet, it is impossible to imagine act has been clear for many years, as a rapid shift to
life without it. The internet has rewoven the fabric of our renewable energy is necessary to stem the worst impacts
daily lives and become a foundation of the global of climate change. Now, costs for renewable energy
economy. On a daily basis, new businesses that use the continue to drop, prices for fossil fuel-based electricity are
internet as their foundation are disrupting and often rising, and leading companies perceive those price cues.
replacing long-standing business models and industries. They are also heeding customers who increasingly value
From music and video to communications and mail, more sustainability. Unfortunately, despite the leadership and
and more of our offline world is moving online. We can innovation demonstrated by green internet pioneers, other
expect that trend to continue and accelerate as the global companies lag far behind, with little sense of urgency,
online population reaches 50% of the world’s projected choosing to paper over their growing dirty energy
population, moving from 2.3 billion in 2012 to an expected footprints with status quo solutions such as renewable
3.6 billion people by 2017[3]. energy credits and carbon offsets while rapidly expanding
their infrastructure.
While the online world appears to grow at the expense of
some traditional business models in the offline world, it is Other internet companies have refused to pay even lip
rapidly creating increased demand for at least one offline service to sustainability, and are simply buying dirty energy
product: electricity. The rapid growth of the cloud and our straight from the grid. Those companies, most notably
use of the internet have produced a collective electricity Amazon Web Services, are choosing how to power their
demand that would currently rank in the top six if infrastructure based solely on lowest electricity prices,
compared alongside countries; that electricity demand is without consideration to the impact their growing electricity
expected to increase by 60% or more by 2020 as the online footprints have on human health or the environment.
population and our reliance on the internet steadily
increase. 2. CHALLENGES & OPPORTUNITIES
Greenpeace second report [2] have analyzed a total of 19
Critically, the internet’s growing energy footprint has thus global IT companies that are leading the sector’s move to
far been mostly concentrated in places where energy is the the cloud. These companies, while less well-known than
dirtiest. Since Greenpeace first report [1], few leading data branded giants like Google or Amazon, operate the data
center operators have taken key steps toward building a centers behind much of the Internet. This update now
green internet, particularly those companies that have includes over 300 data centers in the survey, up from
committed to build a 100% renewably powered platform. approximately 80 in the previous edition. The evaluation
These commitments are having a profound impact in the has been updated to account for how these colocation
11Journal of Computer Application, Volume 5, No. 2, July-December 2014
Ajay Kumar Garg Engineering College, Ghaziabad
companies are pursuing opportunities to play a meaningful helped set a new bar for the industry, illustrating in very
role in driving renewable energy deployment to meet the concrete terms that a 100% renewable internet is within its
internet’s energy needs. reach, and providing several models of intervention for
other companies that want to build a sustainable Internet.
(1) Six major cloud brands – Apple, Box, Facebook,
Google, Rackspace, and Salesforce – have committed
to a goal of powering data centers with 100 %
renewable energy and are providing the early signs of
the promise and potential impact of a renewably
powered internet.
(2) A number of leading brands, most notably Apple and
Facebook, have made significant improvements in
their energy transparency, discarding the previous
creed within the sector of withholding energy data.
Transparency still remains weak overall among many
brands, particularly colocation providers. Facebook continues to grow and dominate the global social
(3) Amazon Web Services (AWS), which provides the media landscape with 1.23 billion monthly active users.
infrastructure for a significant part of the internet, Facebook has made huge strides forward since 2012 to
remains among the dirtiest and least transparent become one of the clear green internet leaders. Radical
companies in the sector, far behind its major improvements in transparency and efforts to deliver
competitors, with zero reporting of its energy or significant wind energy investment in Iowa have helped
environmental footprint to any source or stakeholder. drive Facebook into the top tier of companies creating the
Twitter lags in many of the same areas. green internet. By building on the advocacy it has started
(4) As a result of pressure by three major brands (Apple, with energy utilities to drive more clean energy investment,
Facebook and Google) located in North Carolina, and continuing to find ways to bring renewable energy to
Duke Energy, the largest utility in the US, adopted a scale to power its data centers in North Carolina and Iowa,
Green Source Rider, opening the market to renewable Facebook is setting a clear bar for other major social media
electricity purchases for large customers in North networks and internet companies to follow.
Carolina.
(5) Google maintains its leadership in building a
renewably powered internet, as it significantly
expands its renewable energy purchasing and
investment both independently and through
collaboration with its utility vendors.
(6) Facebook continues to prove its commitment to build
a green internet, with its decision to locate a data
center in Iowa driving the largest purchase of wind
turbines in the world.
(7) Apple is the most improved company since last full
report, and has shown itself to be the most
innovative and most aggressive in pursuing its
commitment to be 100% renewably powered. Google has continued to lead the major internet brands in
purchasing renewable energy at scale to power its massive
3. FEW BRAND NAMES online ecosystem. The company is now reporting electricity
Here, some top brands are discussed.Apple’s aggressive consumption of 3,315 GWh, with 34% of its operations
pursuit of its commitment to power with 100% renewable powered by clean energy. Google’s use of power purchase
energy has given the company the inside track among the agreements to procure clean energy has been adopted by
IT sector’s leaders in building a green Internet. Apple has others in the sector, like Microsoft, and it has successfully
made good on its pledge by building the largest privately influenced utilities in Oklahoma and North Carolina to offer
owned solar farms at its North Carolina data center, working new renewable energy options by using its immense
with its utility in Nevada to power its upcoming data business clout. As Google expands its footprint to Latin
center there with solar and geothermal energy, and America and Asia, it will need to maintain its innovative
purchasing wind energy for its Oregon and California data edge to make sure that it continues to source clean energy
centers. Apple’s commitment to renewable energy has even in countries that feature dirty electric grids.
12Cleaning Online World
[1] Greenpeace. How Clean is your Cloud?Journal of Computer Application, Volume 5, No. 2, July-December 2014
Ajay Kumar Garg Engineering College, Ghaziabad
CURRENT STATUS OF MACHINE
TRANSLATION IN INDIA
Pooja Arora
Assistant Professor, MCA Department, AKGEC, GZB
Abstract— A survey of the machine translation systems that languages. The newspapers in regional languages are
have been developed in India for translation from English to required to translate news in English received from
Indian languages and among Indian languages reveals that the International News Agencies. With the limitations of human
MT softwares are used in field testing or are available as web translators most of this information (reports and
translation service. These systems are also used for teaching
documents) is missing and not percolating down. A
machine translation to the students and researchers. Most of
these systems are in the English-Hindi or Indian language- machine assisted translation system or a translator's
Indian language domain. The translation domains are mostly workstation would increase the efficiency of the human
government documents/reports and news stories. There are a translators.
number of other MT systems that are at their various phases of
development and have been demonstrated at various forums. As is clear from above, the market is largest for translation
Many of these systems cover other Indian languages beside from English into Indian languages, primarily Hindi. Hence,
Hindi. it is no surprise that a majority of the Indian Machine
Translation (MT) systems have been developed for
English-Hindi translation.
1. INTRODUCTION
India has a diverse list of spoken languages. At least 30
Machine Translation activities in India are relatively young.
different languages and around 2000 dialiects have been
The earliest efforts date from the mid 80s and early 90s.
identified. The Constitution of India has stipulated the
The prominent among these efforts are the research and
usage of Hindi and English to be the two languages of
development projects at Indian Institute of Technology
official communication for the national government.
(IIT) Kanpur (http://www.cse.iitk.ac.in/users/rmk/proj/
Additionally, it classifies a set of 22 scheduled languages
proj.html#mt), Computer and Information Sciences
which are languages that can be officially adopted by
Department, University of Hyderabad (http://
different states for administrative purposes, and also as a
www.uohyd.ernet.in/), National Center for Software
medium of communication between the national and the
Technology (NCST), Mumbai (now, Center for Development
state governments, as also for examinations conducted for
of Advanced Computing (CDAC), Mumbai) (http://
national government service. The 22 scheduled languages
www.ncst.ernet.in/) and Center for Development of
are Assamese, Bengali, Bodo, Dogri, Gujarati, Hindi,
Advanced Computing (CDAC), Pune (http://www.cdac.in/).
Kannada, Kashmiri, Konkani, Maithili, Malayalam, Manipuri,
The Department of Information Technology, Ministry of
Marathi, Nepali, Oriya, Punjabi, Sanskrit, Santali, Sindhi,
Communications and Information Technology, Government
Tamil, Telugu and Urdu. English is very widely used in the
of India, through its Technology Development in Indian
media, commerce, science and technology and education.
Languages (TDIL) Project (http://tdil.mit.gov.in) since 1990-
Many of the states have their own regional language,
‘91 and Department of Official Languages, Ministry of
which is either Hindi or one of the other scheduled
Home Affairs, Government of India, since 1989-90 have
languages. Only about 5% of the population speak English.
played instrumental roles by funding these projects. The
In a large multi-lingual society like India, there is a great
following domains have been identified for the
demand for translation of documents from one language to
development of domain specific translation systems:
another. Most of the state governments work in the
government administrative procedures and formats,
respective regional languages whereas the Union
parliamentary questions and answers, pharmaceutical
Government's official documents and reports are in
information, legal terminology and important judgments, and
bilingual form (Hindi/English). In order to have a proper
so on.
communication there is a need to translate these
documents and reports in the respective regional
14Current status of Machine Translation in India
2 MT SYSTEMS IN FIELD TESTING transferred on a non-exclusive basis to Center for
OR AS WEB SERVICE Deveopment of Advanced Computing (CDAC), Noida for
The following machine translation systems are either being commercialization.
used in field-testing or are available as a web service.
Most of these systems are in the English-Hindi language 2.2 MANTRA MT System
domain with exceptions of a Hindi-English and an English- MANTRA (MAchiNe assisted TRAnslation tool) translates
Kannada machine translation system. English text into Hindi in a specified domain of personal
administration, specifically gazette notifications, office
2.1 ANGLABHARTI and ANUBHARTI Technology orders, office memorandums and circulars. Mantra uses
The ANGLABHARTI project was launched by Professor R. Lexicalized Tree Adjoining Grammar (LTAG) to represent the
M. K. Sinha at the Indian Institute of Technology, Kanpur English as well as the Hindi grammar. It uses Tree
in 1991 for machine aided translation from English to Indian Adjoining Grammar (TAG) for parsing and generation. The
languages. Professor Sinha has pioneered MT research in input to the Mantra system can be through text
India. The system’s approach and lexicon is general- documents, outputs of speech recognition programs or
purpose with provision for domain customization. The OCR packages. The Mantra has become part of “The 1999
system has been applied in several domains such as public Innovation Collection” on Information Technology at
health compaign, routine office-correspondance, technical- Smithsonian Institution’s National Museum of American
mannual etc. [1] History, Washington DC, USA. Further details about the
Mantra system can be obtained from the C-DAC website
The first prototype was built for English to Tamil in 1991 (http://www.cdac.in/html/aai/mantra.asp).
and later a more comprehensive system was built for
English to Hindi translation. AnglaBharti is a pattern Initially, the Mantra system was started with the translation
directed rule based system with context free grammar like of administrative document such as appointment letters,
structure for English (source language). It generates a notification, circular issued in Central government from
‘pseudo-target’ (Pseudo-Interlingua) applicable to a group English to Hindi. Currently, the system is being expanded
of Indian languages (target languages) such as Indo-Aryan to cover domains of finance, agriculture, healthcare,
family (Hindi, Bengali, Assamese, Punjabi, Marathi, Oriya, information technology, education and finally to the general
Gujarati etc.), Dravidian family (Tamil, Telugu, Kannada & purpose activities in the Governmental Domain. This
Malayalam) and others. A set of rules obtained through project namely MANTRA-Rajbhasha based on the
corpus analysis is used to identify plausible constituents MANTRA technology developed by C-DAC has been
with respect to which movement rules for the ‘pseudo- funded by the Department of Official Language, Ministry
target’ is constructed. Within each group the languages of Home Affairs, Government of India.
exhibit a high degree of structural homogeneity. The
similarity has been exploited to a great extent in the 2.3 ANUSAARAKA MAT System
system. A language specific text-generator converts the A machine aided translation system (ANUSAARAKA)
'pseudo-target' code into target language text. Paninian among Indian languages has been built with funding from
framework based on Sanskrit grammar using Karak (similar the TDIL project. Anusaaraka is a Language accessor
to case) relationship provides an uniform way of designing rather than a machine translation system in true sense.
the Indian language text generators. They also use an Anusaarakas have been built from Telugu, Kannada,
example-base to identify noun and verb phrasals and Bengali, Marathi, and Punjabi to Hindi. Alpha versions of
resolve their semantics. An attempt is made to resolve all of these have been released so that their field testing
most of the ambiguities using ontology, syntactic & can be carried out. The beta-versions are expected to be
semantic tags and some pragmatic rules. The unresolved released soon.
ambiguities are left for human post-editing. Some of the
major design considerations in design of AnglaBharti have It is domain free but the system has mainly been applied
been aimed at providing an uniform mechanism by which for translating children’s stories. An e-mail server been
translation from English to majority of Indian languages established for the Anusaarakas. It currently holds alpha-
with attachment of appropriate text generator modules versions of Anusaarakas for translating Telugu, Kannada,
becomes feasible. The translation system has also been Marathi, Bengali, and Punjabi into Hindi. To run the
interfaced with text-to-speech module and OCR input. [4] Anusaaraka on a given text, e-mail has to be sent to
The English to Hindi version named AnglaHindi, based on (nandi@anu.uohyd.ernet.in) with the name of the language
the AnglaBharti machine aided translation system has been in the subject line. For example, if 'Telugu' is put in the
web-enabled and is available at (http://anglahindi.iitk.ac.in). subject line, it automatically runs the Telugu to Hindi
The technical know-how of this technology has been Anusaaraka. The output produced is sent back to the
15Journal of Computer Application, Volume 5, No. 2, July-December 2014
Ajay Kumar Garg Engineering College, Ghaziabad
sender. The computer keeps a copy of the output for a www.cfilt.iitb.ac.in/machine-translation/ eng-hindi-mt). Two
later study of results. The text should be in 7-bit ISCII other demo systems can also be run from the site: one for
coding. Similarly help by mail is available if mail is sent Hindi-UNL and another for UNL-Hindi conversion. They
with subject ‘Help’. The systems with complete source are also working on MT systems from English to Marathi
code and language data are available as "free" software and Bengali using the UNL formalism. [5]
and can be downloaded from the website of the Language
Technologies Research Center, Indian Institute of 3 CONCLUSION
Information Technology, Hyderabad (http://ltrc.iiit.net/). MT is relatively new in India – about two decades of R &
Further details about the Anusaaraka system can be D efforts are now showing the results. In comparison with
obtained from their website(http://www.iiit.net/trc/ MT efforts in Europe and Japan, which are at least 3
Anusaaraka/anu_home.html). decades old, it would seem that Indian MT has a long
way to go. However, this can also be an advantage,
The focus in Anusaaraka is not mainly on machine because Indian researchers can learn from the experience
translation, but on Language Access between Indian of their global counterparts.
languages. Using principles of Paninian Grammar (PG), and
exploiting the close similarity of Indian languages, an The time has come when translation activities in Indian
Anusaaraka essentially maps local word groups between languages should look beyond English as the source or
the source and target languages. Where there are the target language. The countries in the Asia-pacific
differences between the languages, the system introduces region are renewing their relations in the area of tourism
extra notation to preserve the information of the source and trade. Development of controlled language machine
language. Thus, the user needs some training to translation systems in these domains from Indian
understand the output of the system. The project languages to the languages of the Asia-pacific region like
originated at IIT Kanpur, and later shifted mainly to the Japanese, Chinese, Korean, Thai and others and vice-versa
Centre for Applied Linguistics and Translation Studies will foster the development of people-to-people contact in
(CALTS), Department of Humanities and Social Sciences, this region.
University of Hyderabad. It was funded by TDIL. It is now
being carried out at the Language Technologies Research REFERENCES
Center, Indian Institute of Information Technology, [1] R.M.K. Sinha. 2005. Integrating CAT and MT in
Hyderabad with financial support from Satyam Computers AnglaBharti-II Architecture. In “Proceedings of EAMT
Private Limited. They are currently attempting an English- 2005”, Budapest, Hungary.
Hindi Anusaaraka MT system. [3] [2] Sivaji Bandyopadhyay. 2004. Use of Machine
Translation in India. AAMT Journal, 36: 25-31.
2.4 SHIVA and SHAKTI MT System [3] R.M.K. Sinha and A. Jain. 2003. AnglaHindi: An
Two machine translation systems from English to Hindi, English to Hindi Machine-Aided Translation System.
Shiva and Shakti are being developed jointly by Carnegie In “Proceedings of MT SUMMIT IX”, New Orleans,
Mellon University USA, Indian Institute of Science, Louisiana, USA.
Bangalore, India, and International Institute of Information [4] Durgesh Rao. 2001. Machine Translation in India: A
Technology, Hyderabad. The two experimental systems Brief Survey. In “Proceedings of SCALLA 2001
have been released for experiments, trials, and user Conference”, Banglaore, India.
feedback. The Example-based Machine Translation system [5] D. Gupta and N. Chatterjee. 2003. Identification of
(Shiva) can be run from the site (http:// Divergence for English to Hindi EBMT. In
ebmt.serc.iisc.ernet.in/mt/login.html) and the machine “Proceedings of MT SUMMIT IX”, New Orleans,
translation system (Shakti) can be run from its own site Louisiana, USA.
(http://shakti.iiit.net). [2]
Mrs. Pooja Arora is working as assistant
2.5 UNL-based English-Hindi MT System professor in MCA department in Ajay
The Indian Institute of Technology, Bombay has Kumar Engineering college. She has
developed a machine translation system for translating completed B.Sc. (computer science) from
Delhi University in 1998 and MCA from
from English to Hindi using the Universal Networking
Banasthali Vidyapith in 2001. Currently
Language (UNL) as the interlingua. The UNL is an she is pursuing ph.d. in computer science
international project of the United Nations University, with from Banasthali Vidyapith.
an aim to create an Interlingua for all major human
languages. IIT Bombay is the Indian participant in UNL.
The MT system can be used at the site (http://
16EVOLUTION OF EDGE TECHNOLOGY IN MOBILE
COMMUNICATIONS FOR GSM - A REVIEW ARTICLE
Sanjeev K. Prasad
Assistant Professor, MCA Department, AKGEC, GZB
sanjeevkps2002@gmail.com
Abstract— Today’s fast growing world needs fast communication, technique and error-tolerant transmission methods,
either it may be voice or data .This calls for a new technology combined with improved link adaptation mechanisms, make
which is faster than all existing technologies in mobile these EGPRS rates possible. This is the key to increased
communication and hence can replace technologies like GPRS spectrum efficiency and enhanced applications, such as
.Enhanced Data for Global Evolution (EDGE) is such a
wireless Internet access, e-mail and file transfers. GPRS/
technology .EDGE is a member of global system for mobile
communications (GSM).In short EDGE is a technology which EGPRS will be one of the pacesetters in the overall wireless
enhances data rates for mobile communications. technology evolution in conjunction with WCDMA. Higher
EDGE not only enhances data rates but also intended for efficient transmission rates for specific radio resources enhance
spectrum utilization which it has passed successfully. This paper capacity by enabling more traffic for both circuit- and
is intended for explaining how theoretical data rates of 384 packet-switched services.
kbps is possible with EDGE technique. And how enhanced data
for global evolution (EDGE) can play an important role in the The goal of EDGE is to boost system capacity, both for
evolution toward wideband code division multiple access real-time and best effort services, and to compete
(WCDMA) and this paper also includes brief details on EDGE
effectively with other third-generation radio access
and modulation scheme used for EDGE. It can be introduced in
two ways: (1) as a packet-switched enhancement for general networks such as WCDMA and cdma 2000.
packet radio service (GPRS), known as enhanced GPRS or
EGPRS, and (2) as a circuit-switched data enhancement called 2. TECHNICAL DIFFERENCES BETWEEN
enhanced circuit-switched data (ECSD). It will only discuss the GPRS AND EGPRS
packet-switched enhancement, EGPRS. The purpose of this Regarded as a subsystem within the GSM standard, GPRS
paper is to describe EDGE technology and how it leverages has introduced packet-switched data into GSM networks.
existing GSM systems and complements WCDMA for further Many new protocols and new nodes have been introduced
growth.
to make this possible .EDGE is a method to increase the
Keyword: GSM, EDGE Technology, GPRS, Packet Data, EGPRS.
data rates on the radio link for GSM. Basically, EDGE only
introduces a new modulation technique and new channel
coding that can be used to transmit both packet-switched
1. INTRODUCTION and circuit-switched voice and data services. EDGE is
EDGE is the next step in the evolution of GSM and IS-136. therefore an add-on to GPRS and cannot work alone
The objective of the new technology is to increase data .GPRS has a greater impact on the GSM system than EDGE
transmission rates and spectrum efficiency and to facilitate has. By adding the new modulation and coding to GPRS
new applications and increased capacity for mobile use and by making adjustments to the radio link protocols,
.With the introduction of EDGE in GSM phase 2+,existing EGPRS offers significantly higher throughput and capacity.
services such as GPRS and high-speed circuit switched GPRS and EGPRS have different protocols and different
data (HSCSD) are enhanced by offering a new physical behavior on the base station system side .However, on the
layer. The services themselves are not modified. EDGE is core network side, GPRS and EGPRS share the same
introduced within existing specifications and descriptions packet-handling protocols and, therefore, behave in the
rather than by creating new ones. same way. Reuse of the existing GPRS core infrastructure
emphasizes the fact that EGPRS is only an “add-on” to the
This paper focuses on the packet-switched enhancement base station system.
for GPRS, called EGPRS.GPRS allows data rates of 115
kbps and, theoretically, of up to 160 kbps on the physical In addition to enhancing the throughput for each data
layer. EGPRS is capable of offering data rates of 384 kbps user, EDGE also increases capacity. With EDGE, the same
and, theoretically, of up to 473.6 kbps. A new modulation time slot can support more users. This decreases the
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