ENERGY AWEAR LOAD BALANCING IN MOBILE AD HOC NETWORK
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
INCON13-IT-050
ENERGY AWEAR LOAD BALANCING IN
MOBILE AD HOC NETWORK
Prof. Uma Nagaraj Shwetal Patil (Student)
Computer Engineering Computer Engineering
Maharashtra Academy of Engg. Maharashtra Academy of Engg.
Alandi (D) Pune, India Alandi (D) Pune, India
Abstract—
Nodes in ad hoc networks can be unfairly burdened to support many packet-relaying
functions, resulting in excessive loads on these hot spots. This load on nodes appear in major
aspect: power consumption. Unbalanced traffic may lead to more delay, packet dropping,
and decreasing packet delivery ratio (PDR). Unbalanced energy consumption leads to node
failure, network partitioning and decreases network lifetime and route reliability. Moreover,
overloaded nodes may deplete their energy in forwarding others packet resulting in unstable
network and performance degradation. In this paper we propose load-balancing schemes
that distribute the traffic on the basis of three important metrics – residual battery capacity,
traffic density and hop count. Route structure, available in the nodes cache, is modified so
that the remaining energy of nodes can be calculated. During the route setup, this metric is
used to select the route with the minimum traffic load and maximum energy. Simulation
results show that the proposed load-balancing schemes significantly enhance the network
performance and outperform one of the most prominent ad hoc routing protocols DSR and
previously proposed load balanced ad hoc routing protocols including EALB in terms of
average End-to-end delay, packet delivery fraction and Throughput.
Keywords— Ad hoc networks, DSR, Load Balancing, Routing Protocols.
I INTRODUCTION
A Mobile Ad hoc Network (MANET) consists of a set of wireless mobile nodes
communicating to each other without any centralized control or fixed network infrastructure.
Each intermediate host between source and target node acts as a router in an ad hoc network
and the topology of the network changes frequently.
The available routing protocols can roughly be classified into three groups: table-driven,
source initiated on-demand, and hybrid routing protocols. However, none of these addresses
load balancing among the routes. In practice, some routes may get congested, while other
routes remain unutilized. This results in poor performance of mobile ad hoc network.
Keeping this in mind, we have tried to develop a protocol, which will balance the load
distribution among various routes. Our proposed protocol is also an on-demand protocol and
has many features similar to that of DSR [1]. Moreover, constraints like lower capacity of
wireless links, error-prone wireless channels, limited battery capacity of each mobile node
etc., degrade the performance of MANET routing protocols. Heavily-loaded nodes may cause
congestion and large delays or even deplete their energy quickly.
In this paper we present novel load-balancing mechanisms/schemes for MANETs that focus
on distributing the traffic on the basis of combination of following three metrics : hop count ,
Route Energy level and average number of packets queued up in the interface queue of a
node lying on the path from source to destination/traffic queue.
1INCON13-IT-050
This paper is organized as follows: In Section 2 we discuss the protocols that are related to
our work. Section 3 presents our Energy Aware Load Balancing Routing Ad hoc (EALB)
protocol. We analyse the EALB Protocol vis-à-vis Dynamic Source Routing (DSR) Protocol.
In Section 4 we present Working of the protocol. In Section 5 the implementation of our
simulation model In Section 6 we present the results obtained from the simulation studies. In
Section 7 we have performance matrices related work. Section 8 concludes this paper.
II RELATED PROTOCOLS
Dynamic Source Routing (DSR)
DSR is a source routing protocol, and requires the sender to know the complete route to the
destination. It is based on two main processes: (a) the route discovery process which is based
on flooding and is used to dynamically discover new routes and maintain them in the nodes
cache, (b) the route maintenance process, which periodically detects and notifies of network
topology changes. Discovered routes will be cached in the relative nodes [1].
+A route from a source node s to a destination node d is a sequence of nodes [s, n1, . .
. , nk , d], where n1, . . . , nk are intermediate nodes located on the path from s to d.
When some node S originates a new packet destined to some other node D, it places in the
header of the packet a source route giving the sequence of hops that the packet should follow
on its way to D. Normally S will obtain a suitable source route by searching its Route Cache
of routes , but if no route is found in its cache, it will initiate the Route Discovery protocol to
dynamically find a new route to D. In this case, we call S the initiator and D the target of the
Route Discovery. For example, Figure 1 illustrates an example Route Discovery, in which a
node A is attempting to discover a route to node E. To initiate the Route Discovery, A
transmits a ROUTE REQUEST message as a single local broadcast packet, which is received
by (approximately) all nodes currently within wireless transmission range of A. Each
ROUTE REQUEST message identifies the initiator and target of the Route Discovery, and
also contains a unique request id, determined by the initiator of the REQUEST. Each ROUTE
REQUEST also contains a record listing the address of each intermediate node through which
this particular copy of the ROUTE REQUEST message has been forwarded. This route
record is initialized to an empty list by the initiator of the Route Discovery.
When another node receives a ROUTE REQUEST, if it is the target of the Route Discovery,
it returns a ROUTE REPLY message to the initiator of the Route Discovery, giving a copy of
the accumulated route record from the ROUTE REQUEST; when the initiator receives this
ROUTE REPLY, it caches this route in its Route Cache for use in sending subsequent
packets to this destination. In returning the ROUTE REPLY to the initiator of the Route
Discovery, such as node E replying back to A[2].
2INCON13-IT-050
III ENERGY AWARE LOAD BALANCING ROUTING IN AD HOC PROTOCOL
(EALB)
Energy aware load balancing (EALB) protocol for efficient data transmission in mobile ad
hoc networks. We also define a new metric for routing called traffic density to represent the
degree of contention at the medium access control layer. During the route setup, this metric
is used to select the route with the minimum traffic load and maximum nodes energy. EALB
protocol requires that each node maintain a record of the latest traffic queue estimations at
each of its neighbors in a table called the neighbourhood table. This table is used to keep the
load information of local neighbors at each node. This information is collected through two
types of broadcasts. The first type of broadcast occurs when a node attempts to discover route
to a destination node. This type of broadcast is called route request. The second type of
broadcasting is the hello packet broadcasting. In the event that a node has not sent any
messages to any of its neighbors within a predefined timeout period, called the hello interval,
it broadcasts a hello message to its neighbors. A hello packet contains the sender node’s
identity and its traffic queue status. Neighbors that receive this packet update the
corresponding neighbour’s load information in their neighbourhood tables. If a node does not
receive a data or a hello message from some of its neighbors for a predefined time, it assumes
that these nodes have moved out of the radio range of this node and it changes its
neighbourhood table accordingly. Receiving a message from a new node is also an indication
of the change of neighbour information and is handled appropriately.
A number of routing protocols proposed for MANETs use shortest route in terms of hop
count for data transmission. It may lead to quick depletion of resources of nodes falling on
the shortest route. It may also result in network congestion resulting in poor performance.
Therefore, instead of hop count a new routing metric is required that can consider the node’s
current traffic and energy status while selecting the route. The idea is to select a routing path
that consists of nodes with higher residual energy power and hence longer life. We define the
required parameters, as follows: The terms used in this paper have been defined as follows:
1) Route Energy (RE): The route energy of a path is the minimum of residual energy of nodes
(rei) falling on a route. Higher the route energy, lesser is the probability of route failure due to
exhausted nodes.
2) Traffic queue (tq): The traffic queue of a node is the number of packets queued up in the
node’s interface. Higher is its value, more occupied the node is.
3) Traffic density (TD): The traffic density of a node i is the sum of traffic queue qi of node i
plus the traffic queues of all its neighbors
4) Hop count (HC): The HC is the number of hops for a feasible path.
5) Traffic Cost: The traffic cost of a route is defined as the sum of the traffic densities at each
of the nodes and the hop count on that particular route.
6) Weight Route: The weight Route is calculated from Route energy and traffic cost.
The route with highest weight value is selected as the routing path and RREP packet is sent
back towards the source node on the selected path.
3INCON13-IT-050
Traffic queue: The traffic queue of a node is defined as the average value of the interface
queue length measured over a period of time. For the node i , it is defined as the average of N
samples over a given sample interval
N
∑ qi(k )
qi = k =1
N
th
where qi(k) is the k sample of the queue length. qi is the average of these N samples. The
greater the value of N; the better is the estimation of the traffic.
Traffic density: The traffic density of a node i is the sum of traffic queue qi of node i plus the
traffic queues of all its neighbors, formally
Q(i ) = ∑ qj
∀jεN ( i )
where N(i) is the neighborhood of node i and qj is the size of the traffic queue at node j :Q(i)
is the sum of traffic queues of all the neighbors of node i plus that of node i itself.
Hop cost : This factor captures the transmission and propagation delay along a hop.
Traffic cost : The traffic cost of a route is defined as the sum of the traffic densities at each of
the nodes and the hop costs on that particular route. The traffic cost of some route r is given
by the following expression
C (r ) = ∑ Q(i ) + ∑ hij
iεr i , jεr ,iadjj
where i, j are nodes on route r. hij is the hop cost along i and j. i adj j refers to the fact that
node j is adjacent to node i.
IV WORKING OF THE PROTOCOL
In this paper tends to determine the routes in such a way that the routes consisting of nodes
with lower Route Energy Level are avoided for data transmission even if they are short and
less con-gested. This scheme tries to make a fair compromise between three route selection
parameters i.e. hop count, route energy level and traffic load.
A MANET can be represented as an undirected graph G(V, E) where V is the set of nodes
(vertices) and E is the set of links (edges) connecting the nodes. The nodes may die because
of depleted energy source and the links can be broken at any time owing to the mobility of
the nodes.
ALL n or n є V, n has an associated traffic queue tq(n) and residual battery energy rei. A path
between two nodes s and d is given as
P(s, d) = (s, e(s, a), a, e(a, b), b, ......., e(s, d), d)
It can be emphasized that a path between any two nodes is a set consisting of all possible
paths between them. Formally,
P(s, d) = {P0 , P1 , ...., Pn}
Where each Pi is a candidate path between s and d.
Let HC(Pi ) be the hop count corresponding to path Pi between s and d. Weight of path Pi
defined as:
W(Pi)= RE(Pi) - ATD(Pi) (1)
4INCON13-IT-050
where RE( Pi) = min {ren1, ren2, ..., renm} and n1, n2,..., nm are the nodes making up the path.
ATD(Pi ) =(td(n1)+td(n2)+ ...+td(nm))/m-1 (2)
The fields having adverse contribution to traffic distribution are built into negative
coefficients in Equation (1).
The idea is to find a path from source to destination with maximum weight such that from the
very beginning the path determined is energy efficient and there is a fair compromise
between a short route and a light-loaded route.
We call this path Energy Aware Load-balanced Path (EALB).
Supposing that i є {0,1,2,…,n}, P(s,d) = {P0, P1,…, Pn} for given source s and destination d,
we can define the problem mathematically as:
EALB (s,d) = Pi with
W(Pi) = max {W(P1), W(P2),…, W(Pn)} (3)
The route with highest weight value is selected as the routing path.
Example:
Table 1. Comparison of schemes for high vales of route
5INCON13-IT-050
Route Discovery
EALB is an on-demand protocol and the route discovery process is similar to that of DSR.
When a source S has a packet to transmit to a destination D for which there is no entry in the
routing table RT, a route request RREP process is initiated. Each node has route table RT is
used to maintain a record of the latest traffic queue TQ estimations at each of its neighbors in
a table called the neighborhood table. In the route request RREQ process, the source S
broadcasts route request packets are broadcasted. A route request packet contains a sequence
number seqid, a source id Sid and a destination id Did Sequence number is the route record,
containing the sequence of nodes taken by the route request packet RREQ packet {seqid, Sid,
Did}. as it is propagated through the ad hoc network during the route discovery[3]. where
n1, . . . , nk are intermediate nodes located on the path from s to d. An intermediate node
listening to the request, broadcasts the request further, after appending its own traffic density
to the packet and energy capacity. RREQ packet {seqid, Sid, Did, Td} this node does not
entertain any further requests with the same sequence number Seqid, source id Sid. This
process continues until the request packet reaches the destination.
After receiving the first request, the destination waits for a fixed time-interval (typically 50
ms) for more route request packets (carrying the source to destination routes) to arrive. When
the preset timer expires after receiving the first route request packet, the destination node
selects the best route from among the candidate routes {c1,c2…cn} and sends a route reply
RREP to the source S with appending the weight value[5].
Route selection for TCP traffic
The TCP sender assumes that all packet losses are caused by congestion for a given TCP
traffic-source, our route selection method is based on the number of hops and the traffic cost
of that route. Whenever a choice has to be made, we select the route with the smallest number
of hops. If there is more than one route with the same minimum number of hops, we select
the route with the minimum traffic cost. This route is the one that results in the maximum
throughput, as it has the least contention at the MAC level.
Route selection for non-TCP traffic
For each of the candidate routes, the destination determines the route’s traffic cost. The route
with minimum value of traffic cost is selected.
Route maintenance
Each node uses a link layer detection scheme to infer the status of the link. A node not
receiving passive acknowledgement or any hello packets from its neighbors for a certain
interval is also an indication of link failure. If a link failure occurs during a data transmission
session, the source is informed of the failure via a route error packet. On receiving a route
error packet, the source initiates a new route search.
6INCON13-IT-050
V. SIMULATION MODEL
A. Congestion model
The load in the network is varied by changing the length of the interface queue at each of the
nodes in the topology. The length of each interface queue is maintained in queue files. Also,
this scheme helps us to control the load at each of the nodes independent of the other nodes.
Study of the network behaviour under such conditions is necessary, because in the ad hoc
environment, it is very likely that some of the nodes are heavily loaded where as others are
lightly loaded. The candidate protocols were studied under the conditions of low, medium
and heavy loads. We have assumed that each interface queue can hold up to 50 packets
awaiting transmission and is managed in a drop tail fashion. Whenever the queue length
exceeds this limit, the packets that arrive last are dropped.
B. Link failure model
The nodes in the network are connected through bidirectional links. The link failure module
periodically breaks the links on the active routes by setting their states to ‘down’ and back to
‘up’ after a specified delay, depending on the mobility pattern. The faster the change in the
topology, the greater is the frequency of link failure. It is also assumed for simplicity that on
a multi-hop route, only a single link can fail on a particular route at any time.
C. Transmission model
We have simulated both TCP and non-TCP (UDP) traffic over ad hoc networks. We have
chosen CBR (Constant Bit Rate) data traffic as the representative non-TCP traffic. The CBR
source is assumed to transmit data at 4 bits/s. For each run over a given scenario, the data
transmission is done between the same two nodes in order to ensure uniformity.
Remaining energy level
The remaining battery power of a route's nodes can be an important metric in the selection of
that route. Thus a route with a maximum remaining battery power in its nodes can be an ideal
route with respect to energy level. Moreover, despite the fact that sometimes a route may
have a high remaining energy level; it may have some nodes with very low energy levels too.
VI IMPLEMENTATION
We create queue files for each of the nodes in the topology. Each queue file entry contains
four values: time, the length of the interface queue, and the traffic density of node i, and
remaining battery power of a route's nodes and the time to transmit an arriving packet under
the given load conditions The route discovery module first loads the scenario file using the
scenario update module. The scenario file decides how many routes are there between the
source and destination and the number of hops in each route. Then the route discovery
module sends route discovery packets on all the possible routes between the source and
destination.
7INCON13-IT-050
Fig 5 System Architecture Diagram
The intermediate nodes add their id to this packet and forward the packet to the next node.
The route discovery packet that reaches the destination first is selected by the destination, and
a route reply packet is sent back to the destination containing the source route. Once a route
to the destination is found, the source module starts sending the data to the destination via
intermediate node modules. At each node, the packets are buffered until they can be
transferred to the next node. Before a packet can be sent to the next node, the link failure
module checks whether it is time for the link to be broken. If the time is reached, the link is
made down. The data packets on this link are dropped and an ERROR packet is sent to the
source node to indicate that the host is unreachable. The source node can then restart the
route discovery procedure.
VII SIMULATION RESULTS
We have used ns-29 for our simulations. As mentioned earlier, we have performed our study
with DSR and the proposed protocol (EALB). The DSR protocol in ns-2 maintains a send
buffer of 64 packets used in route discovery. The maximum waiting time in the send buffer
during route discovery is 30 seconds. If the packet is in the send buffer for more than 30
seconds, the packet is dropped. The size of the interface buffer of each node for simulation is
taken as 50 packets. We have taken Pause time in a rectangular grid of dimensions 600m x
600m. We run each simulation for 600 seconds. We have used a constant bit rate (CBR)
source as the data source for each node. We have considered 12 source nodes for simulation,
each node transmitting packets at the rate of four packets per second, with a packet size of
512 bytes.
8INCON13-IT-050
A. Performance metrics
(i) Packet Delivery Fraction: It gives the ratio of the data packets delivered to the
destination to those generated by the sources, which reflects the degree of reliability of the
routing protocol.
(ii) Throughput: Throughput is measured as the ratio of the number of data packets
delivered to the destination and the number of data packets sent by the sender.
(iii) End-to-end delay: End-to-end delay is the time between the reception of the last and
first packet / total number of packets reaching the application layer.
Figure 1-3 show the relative performance of EALB and DSR for different number of mobile
nodes and pause time.
Fig 1. % of Packet Delivered vs. Pause Time (seconds) with 30 nodes.
Fig 2. Throughput vs. Pause Time (seconds) with 30 nodes.
9INCON13-IT-050
Fig 3. End-to-end Delay vs. Pause Time (seconds) with 30 nodes.
VIII CONCLUSION
We have proposed a new routing protocol called the EALB protocol. This route selection
helps the routing protocol to avoid congested routes. This helps to uniformly distribute the
load among all the nodes in the network, leading to better overall performance. Since the
DSR protocol does not take into account any kind of load information during the route
discovery procedure, some of the nodes in the network may get highly overloaded leading to
fast battery exhaustion and high end-to-end delay. In this protocol the three parameters
responsible for final route selection are - the average traffic queue, the route energy, and the
hop count. And, the weights corresponding to these parameters may be fixed or adaptive to
the network status, depending upon the load balancing scheme. By taking these three
parameters together the traffic is deviated from high loaded routes towards routes possessing
higher energy and less loaded.
10INCON13-IT-050
REFERENCES
[1] D.B. Johnson, D.A. Maltz, Dynamic source routing in ad-hoc wireless networks, in: T.
Imielinski, H. Korth (Eds.), Mobile Computing, Kluwer, Dordrecht, 1996, pp. 153–181.
[2] J. Broch, D.B. Johnson, D.A. Maltz, The dynamic source routing protocol for mobile ad hoc
networks, Dec 1998, IETF internet draft, draft-ietf-manet-dsr-01.txt
[3] C.E. Perkins, E.M. Royer, Ad-hoc on-demand distance vectorrouting, Proc. Second IEEE
Workshop Mobile Comput. Syst. Appl. Feb (1999) 90–100.
[4] Shashank Bharadwaj, Vipin Kumar, Ankit Verma “A Review of Load Balanced Routing Protocols
in
Mobile Ad hoc Networks” , International Journal of Engineering Trends and Technology- July to Aug
Issue 2011.
[5] M. Gerla, S.-J. Lee, dynamic load-aware routing in ad hoc networks, Proceedings of IEEE ICC
2001, Helsinki, Finland, June 2001, pp. 3206–3210
11You can also read
