DSR based Load Balancing Routing in MANETs using MATLAB

ISSN(Online): 2320-9801 DSR based Load Balancing Routing in MANETs using MATLAB Sakshi Dhawan 1, Sudhir Vasesi 2 M. Tech Scholar Department of Electronics and Communication, D.C.R.U.S.T, Murthal, Haryana, India 1 Assistant Professor, Department of Electronics and Communication, D.C.R.U.S.T, Murthal, Haryana, India 2 ABSTRACT: A MANET is a infrastructure-less network that can exchange information to each other with limited resources and these limited resources creates many challenges in MANETs. In MANETs providing a route to the traffic is an extreme challenge as there are problems. The main challenge in MANET is to find route in the cases of link breakage. As all nodes have make decision on the information collected, this causes the node imbalance problem in the network. While providing the route to the nodes sometimes the central node has to pass more traffic which will cause the problem of Load-balancing. These limitations of resources in MANETs needs an efficient routing protocol which uses the resources skillfully. Out of many traditional routing protocol, DSR an on-demand routing protocol has lower routing overhead. Some additional features are added to the DSR protocol to bring flexibility and robustness using MATLAB. The performance of the network will be evaluated on the basis of QoS metrics. Considering route balancing as routing policy and improve DSR functionalities like end to end delay, latency or packet delivery ratio and throughput. KEYWORDS: DSR, Load-balancing, throughput, end-to-end delay, latency I. INTRODUCTION A Mobile Ad Hoc Network (MANET) forms a infrastructure-less network dynamically with the independent mobile hosts without the assistance of centralised infrastructure. The major application areas of MANETs are military operations, emergency rescue operation, law enforcement, vehicular networking, deep rural areas and convention centres[3]. MANET is a self-organising network that merges the wireless communication with a high degree nodemobility. Nodes together forms an arbitrary topology. In other networks to perform the basic operation like routing, packet forwarding, they have only one dedicated node for it, but in MANETs every node can perform these basic operation. Nodes in MANET are multi-hop means through the wireless link nodes that come in the radio's range can communicate directly, where as nodes which are not in the range rely on intermediate node to act as router for them[1]. Routing in MANETs is to select an efficient path to send the traffic from source to the destination node. Each node decides its own route. In MANETs providing a route to the traffic is an extreme challenge as there are problems like limited communication resources, node mobility and larger number of nodes[3]. These limitation of resources in MANETs needs an efficient routing protocol which uses the resources skilfully. As in MANETs the nodes works both as a host and router so it is difficult for the network provider to maintain an appropriate Quality of Service for MANETs due to the dynamic behaviour of the network topology. QoS in MANETs is the network ability to provide its user satisfaction. The QoS can be measured by the parameters such as bandwidth, probability of packet loss, throughput, end-to-end delay and jitter[4]. In this paper we presented a load balancing DSR routing protocol. Some additional features are added to the DSR protocol to bring flexibility and robustness. Considering route balancing as routing policy and improve DSR functionalities like end to end delay, packet delivery ratio, latency and throughput. All the previous routing solutions deal with the best-effort data traffic. II. PROBLEM STATEMENT MANET routing protocol are based on different design philosophies and proposed to meet certain requirements. Thus, the performance of routing protocols may vary dramatically with the variations of network. Routing is the key Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15425

ISSN(Online): 2320-9801 feature of mobile ad hoc network. And providing a efficient routing protocol for MANETs is a challenge because of its dynamic environment. The challenges of MANET routing protocol are mobility, bandwidth constrained, load imbalance and security. Hence, the aptness of the routing protocols depends on various parameters like, traffic load, network size. The limited resources in MANETs make it difficult to select the one which can meet the requirements. In this paper we are considering the load imbalance problem. The cause of load imbalance can be more on a low powerful node in the scenario which makes central node to transmit more traffic. The job completion in MANET becomes complex, when nodes get huge load with less processing capabilities and which do not have any other way to transmit the load. The possibility of imbalance of load can be due to when some nodes get more traffic or overloaded and some nodes remain idle. Nodes which has higher power finishes its work quickly and becomes idle before a less powerful node, assigned extra work, consuming more energy. A lot of routing approaches are developed for load balancing in mobile ad hoc network. The traditional routing protocol like DSR, AODV, DSDV are not able to balance the load. In this paper, we have proposed a DSR based load balancing routing protocol. III. DSR Dynamic source routing is a reactive routing protocol. It is an on-demand protocol means when a request is made only then it works. The DSR has two main operation: Route Discovery and Route Maintenance. In Route Discovery a node will discover its shortest path, if it doesn't have a valid route. It will broadcast a route request containing its own address and the destination address. Each node will receive the request and check if it has a path to the destination requested. If it has the route it will send the packet to the destination and will get a route reply. If it doesn't have a valid route the node will insert its address and broadcast it again. In this mechanism by which a node S wishing to send a packet to a destination node D obtains a source route to D. Fig 1: Route Discovery[7] Route Discovery is used only when S attempts to send a packet to D and does not already know a route to D as shown in figure 1. Route Maintenance, in this it gives intimation if there is a link breakage in the network. When it discover a link breakage it will send a route error to the source node[4]. In this mechanism by which node S is able to detect, while using a source route to D, if the network topology has changed such that it can no longer use its route to D because a link along the route no longer works as shown in figure 2. When Route Maintenance indicates a source route is broken, S can attempt to use any other route it happens to know to D, or can invoke Route Discovery again to find a new route. Route Maintenance is used only when S is actually sending packets to D. Fig 2: Route maintenance[7] Route Discovery and Route Maintenance each operate entirely on demand. In particular, unlike other protocols, DSR requires no periodic packets of any kind at any level within the network. For example, DSR does not use any periodic routing advertisement, link status sensing, or neighbour detection packets, and does not rely on these functions from any underlying protocols in the network. As nodes begin to move more or as communication patterns change, the routing packet overhead of DSR automatically scales to only that needed to track the routes currently in use. In response to a single Route Discovery (as well as through routing information from other packets overheard), a node Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15426

ISSN(Online): 2320-9801 may learn and cache multiple routes to any destination. This allows the reaction to routing changes to be much more rapid, since a node with multiple routes to a destination can try another cached route if the one it has been using should fail. This caching of multiple routes also avoids the overhead of needing to perform a new Route Discovery each time a route in use breaks[7]. Table1 : Comparison between AODV and DSR routing protocol Parameter type AODV DSR Protocol type Ad hoc on-demand distance vector routing Dynamic Source routing Routing approach Reactive Reactive Route Single route Multiple route Throughput Best Better than DSDV Packet delivery ratio High Performs well when the number of nodes is less but it declines drastically when the numbers of nodes are increased Routing overhead More than DSR Lower Normalised routing load (NRL) Consistent & worse NRL when increasing no. of nodes Much higher than AODV when network load is increased A. Caches DSR uses two types of caches: path cache and link cache. Path cache is easy to implement and easily guarantee that routes are loop free. In path cache, as each path is stored separately and there is no sharing in the data so it larger space for storage[9]. When a route is needed, the path cache data structure can be efficiently searched for any path leading to that destination. A link cache has more potential to utilize the route information more efficiently compared with a path cache. In path cache, if a link is broken, a complete route will be removed. But in link cache, only the broken link is removed. The figure shows example of both link and path cache. In path cache, when link A--C is broken, then there will be no route to destination D and F exist. If a route to the destination D or F is desired, a route discovery process has to be initiated. Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15427

ISSN(Online): 2320-9801 Fig 3: Path Cache and Link Cache[10] While in link cache, if link A--C is removed, it still has route A-B-C-D or A-B-C-E-F to the destination D or F. So a route discovery can be avoided. Therefore, with a link cache, potential reduction in the costly route discovery operation can be expected[10]. B. Dijkstra Algorithm Dijkstra's Algorithm is a solution to the single-source shortest path problem in graph theory. Works on both directed and undirected graphs. However, all edges must have nonnegative weights. It computes length of the shortest path from the source to each of the remaining vertices in the graph. Fig 4: Minimum Cost path tree The Figure 4 shows how minimum cost to a destination can be calculated. The blue circles represent "nodes" or "vertices" and the black lines are "edges" or "node paths. Each edge has a cost associated with it. The node 1 is the source node and the shortest path calculation is done from this node. We will take different nodes as a destination for the calculation of path. Table 2 : Shows the cost calculation to the destination. Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15428

ISSN(Online): 2320-9801 If the destination is node 2 then the cost for this node is 2. If the destination is % then the cost is 5 and so on[11]. C. QoS metrics Metrics are the cost values used by routers to determine the best path to a destination network. In dynamic routing protocols several factors help in deciding the best path or shortest path to a particular destination. These factors are called as metrics and algorithm. Metrics are the network variables used in deciding which path is preferred in terms of those metrics. For some routing protocols these metrics are static and may not be changed. For other routing protocols these values may be assigned by a network administrator. QoS metrics is the base parameter of the quality of network. QoS parameter includes bandwidth, jitter, battery life, end-to end delay, packet delivery ratio, reliability, load. a) Bandwidth: It is defined as the amount of data that can be transmitted in a fixed amount of time. It is measured in terms of bits per second. Links that support higher transfer rates like gigabit are preferred over lower capacity links 56kb. The path with higher bandwidth are chosen as the best route. b) Load: Load is variable value, generally measured over a five second window indicating the traffic load over a specific link. Load measures the amount of traffic occupying the link over the time frame as a percentage of the link's total capacity. As traffic increases, this value increases. Routing protocols can recognise when a path is becoming congested and use an alternate path during that time. c) Packet delivery ratio: Packet delivery ratio is the total number of unique data packets arrive at the destination divided by the total number of data packets sent from source. d) Throughput: It is the ratio of packets delivered to the total number of packets sent e) Average end to end delay: The average time it takes a data packet to reach the destination. This metric is calculated by subtracting time at which first packet was transmitted by source from time at which first data packet arrived to destination[25]. IV. LOAD BALANCING In MANETs, load balancing is a critical issue which can reduce the network performance while consuming more energy. Load balancing refers to the transfer of traffic from the source till the destination without burdening a particular node. Means there should be no burden on particular node to transmit more traffic than the other. In MANETs all nodes have to make decisions collectively. In such environment load imbalance can occur. Sometimes in a network a powerful node finishes its assigned job quickly and become idle before a less power node, assigned with extra work load or occupied most of the time, consuming more energy. The other cause for load balancing problem can be finding the shortest route in the scenario which makes central node to transmit more traffic. If the load is not balanced then it Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15429

ISSN(Online): 2320-9801 will cause various problems like delay in packet delivery, increase in packet drop ratio, affect the overall throughput, as well as increasing the end -to-end delay[12]. So a routing protocol is desired to overcome this problem by defining the right route for the nodes to continue. The traditional routing protocol can only provide routes appropriate for best effort traffics. They are not efficient in providing the guaranteed QoS. MANET have various network characteristics and constraints which make it difficult to achieve the required QoS. Quality of service is a set of services provided by the network according to the user satisfaction. To overcome the problems faced by the traditional routing protocol like not supporting QoS and load imbalance a QoS routing is adapted. In this thesis we will add some additional features to the DSR protocol to bring flexibility and robustness which will help us in improving the performance of DSR. A. Load balancing and its purpose in MANET The aim of load balancing is to balance the load among the network. As MANET is dynamic in nature due to the topology changes one node can detect congestion while transmitting data. When the routing protocol in MANET are not conscious about the load imbalance, the network will face long delay, high overhead, many packet losses. Relaying on a specific subset of nodes, while transferring large quantity of data causes congestion and deteriorates the whole path if, a node fails early during forwarding. Overburden some of the nodes influence not only the battery power of those partial nodes to be used up prematurely but causes high end-to-end delay. In such scenarios, a network demand an efficient load balancing scheme to be implemented so that the data the data can distributed reasonably. The main purpose of load balancing is to avoid the use of a specific path or routes to transfer data[3]. B. Types of load balancing 1. Based on the path: Load balancing scheme based on the path works by selecting nodes with less number of active route to forward data. The node which takes part in forwarding data acts as a forwarding node. The active node is prone to more failure as compare to the normal node as its resources are shared. This type of load balancing scheme is not a most effective type as the energy consumption and available resources cannot be correctly determined. 2. Based on Delay: The delay is measure of difference in time when data transmit by the sender and the time when the receiver, receives it. The time delay gives information about the length of the path, shortest path give lesser delay than the larger one. When the packet remains in a queue for longer interval of time, it shows that the node is not having enough bandwidth. 3. Based on Traffic: This type is most effective as the network traffic is evenly distributed among nodes or paths. The term, load in a network is defined as the number of bytes of packets transmitted by the node and the number of nodes which it is currently receiving the packets. When the node gets overloaded, it will exclude it from route and reset all the paths. 4. Based on computed weights of the multiple paths: The weighted approaches computes the weights of the paths in terms of certain predefined parameters by computing the values at each node. The path having the best metrics is selected over the other. The selected path must ensure congestion free, optimal and minimum end to end delay. V. PROPOSED METHOD The aim is to balance the load and improve the performance metrics by adding some features to the Traditional DSR protocol. This method works on link cache. DSR has two types of caches: path cache and link cache. A link cache has a conventional graph data structure in which link is referred to as a cached data unit[12]. Link cache utilize the route information more efficiently. If there is no link mechanism present then the stale link will cause major performance degradation. Fig 5: Routing that contains link costs as well as nodes Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15430

ISSN(Online): 2320-9801 Each link in the link cache is assigned a cost value as shown in figure 5. Every link in the node should have the same cost so as to calculate the shortest path. Dijkstra algorithm is used to find the shortest path as it is a graph search algorithm. As we can change the cost according to different parameter like energy etc. The nodes should know, in a network, about the link cost while searching for the route so as they can be assigned different values of cost. Nodes should be aware of all these cost values exchanges. In our method the link is transferred through DSR header and DSR header contains the sequence of nodes. Now we proposed our load balancing method to route the best effort packets. A centrality metrics is proposed which determines nodes importance in the network. And the centrality metrics calculates the number of edges that connect a node to the other node in a network. Consequently, the node neighbour count is the centrality measure. The routing criteria is: According to the equation the node centrality measure will maintain an updated neighbour count. When a packet is received at the node this is added up in MAC protocol list and sender node is also added to the list, if not already included in it. A the link breakdown it is reported to the node, it will remove that link from its neighbour list. Fig 6: Asymmetric link cost between node A and Node B A method to assign values to link costs is proposed to enable the application of the centrality metric. As the figure 6 shows cost of the link between node A and node B. Node B has four neighbours (including node A) and similarly node A has five neighbours. Hence the link cost for node B is 4 and link cost for node A is 5. Therefore link cost is asymmetric. This problem causes imbalance so we proposed another metric for the link cost. This assigns the link cost to be equal to the sum of cost of the two node centralities which make it symmetric and simple as shown in figure 7[4]. Fig 7 : Symmetric link cost between node A and node B Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15431

ISSN(Online): 2320-9801 The proposed method performance is checked on the basis of the QoS metrics i.e., packet delivery ratio, end-to-end delay and throughput. VI. SIMULATION RESULTS MATLAB software is used as a simulator. The scenario for our method is 50 nodes move in the area of 100 X 100 using the Random Waypoint mobility. A. Cost calculation - Start id is 5. -Finish id is 3. -The path it travels is from 5-32-29-3. -The cost for this path is 66.1641 Fig 8: Cost calculation through shortest path algorithm Figure 8 shows the shortest path calculation on the basis of cost with the help of dijkstra algorithm and load balanced algorithm. B. Packet delivery ratio Fig 9 : Packet delivery ratio Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15432

ISSN(Online): 2320-9801 Figure 9 shows the packet delivery ratio of the proposed method. As the traffic increases the packet delivery ratio decreases. The X axis is labeled as traffic which is in Kbps. The Y-axis is labeled as packet delivery ratio. The delivery ratio for Load balanced DSR is higher than the DSR. As the traffic increases the delivery ratio of both the protocols decreases. C. Throughput Fig 10: Throughput Figure 10 shows the throughput of the model created. The X-axis shows throughput and the Y-axis shows time. The throughput of load balanced DSR is better than the DSR. D. Latency or end-to-end delay Fig 11: Latency Figure 11 shows the latency of the proposed method. The X-axis labeled as Latency and the Y-axis as traffic. The graph shows as the traffic increases the Latency for the DSR is more than the latency for the load balanced DSR. Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15433

ISSN(Online): 2320-9801 VII. CONCLUSION AND FUTURE WORK In this thesis, we have performed performance analysis of DSR routing protocol and DSR based load balancing algorithm. Throughput, end-to-end delay(latency) and packet delivery ratio are used to analyze the protocols. To do so, we presented an effective graph based method that enables applying varied routing protocol policies to DSR. Shortest path is calculated with the minimum cost criterion. Best effort traffic flow is used which do not have any specific requirement. This best effort traffic flows through the network edge using centrality metrics. A node centrality metric is used, which is defined as the number of its neighbour in the network and applied to the DSR. Symmetric cost assignment is the basis to balance the load between the nodes and in the network. All the parameters which provide QoS are shown through graph. And we conclude that our proposed method performs better in MATLAB. As a future scope for this thesis, we can apply the same algorithm to the real time traffic as we are getting better result in best effort traffic. The parameters like bandwidth, power and energy can be considered in the simulation to make the network more reliable. REFERENCES 1. Al-Sakib khan Pathan "Security of Self-Organizing Networks MANET, WSN, WMN, VANET" Auerbach Publications 2011 by Taylor and Francis Group, LLC 2. Xiaoyan Hong, Kaixin Xu, Mario Gerla "Scalable Routing Protocols for Mobile Ad Hoc Networks" ONR MINUTEMAN project under contract N00014-01-C-0016, in part by DARPA under contract DAAB07-97-C-D321. 3. Manu J Pillai, M P Sebastian and S D Madhukumar "Dynamic Multipath Routing for MANETs A QoS Adaptive Approach" 2013 IEEE. 4. Hanif Maleki, Mehdi Kargahi and Sam Jabbehdari "RTLB-DSR: a Load-Balancing DSR Based QoS Routing Protocol in MANETs" 2014 4th International Conference on Computer and Knowledge Engineering (ICCKE). 5. Zhijing Xu, Kang Wang, Liu Qi "Adaptive Threshold Routing Algorithm with Load-balancing for Ad Hoc Networks" Proceedings of the 2009 International symposium on Web Information Systems and Applications. 6. Suman lata "A Survey On Load Balancing Appraoch In MANET" Term Paper, 2010, 7 Pages Computer Science - Internet, New Technologies, Munich, GRIN Verlag. 7. David B. Johnson, David A. Maltz, Josh Broch "DSR: The Dynamic Source Routing Protocol for Multi-Hop Wireless Ad Hoc Networks" Computer Science Department Carnegie Mellon University Pittsburgh, PA 15213-3891 Available from: http://www.monarch.cs.cmu.edu/ 8. Ramandeep, Sangeeta Monga"Comparison of MANET Routing Protocol-A Review" IOSR Journal of Electronics and Communication Engineering (IOSR-JECE). 9. Soon Don Kwon, Jung Shin Park, Jai Yong Lee "A New Route Cache Scheme in On-Demand Routing Protocols for MANET" Korea science and engineering foundation under Grant No.1999-2-303-005-3, ICITA2002 ISBN: 1-86467-114-9. 10. Wenjing Lou And Yuguang Fang "Predictive Caching Strategy for On-Demand Routing Protocols in Wireless Ad Hoc networks" Wireless Networks 8, 671 679,2002 Kluwer Academic Publishers. Manufactured in The Netherlands. 11. Pooja Singal R.S.Chhillar "Dijkstra Shortest Path Algorithm using Global Positioning System" International Journal of Computer Applications (0975 8887)Volume 101 No.6, September 2014. 12. Shobha.K.R and Dr.K.Rajanikanth "Analysis Of Performance Of Dsr Using Different Types Of Cache In Dynamic Environment" International Journal of Distributed and Parallel Systems (IJDPS) Vol.2, No.1, January 2011. Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0408105 15434