Mobile ad hoc networks (MANET) are infrastructure-less networks. The dynamic topology and multi-hop communications make routing a challenging task. Because MANET nodes are characterized with limited resources, heavily-loaded nodes may make up a bottleneck situation lowering the network performance. This necessitates the requirement of efficient distribution of load in the network. In this paper we propose load-balancing schemes that distribute the traffic on the basis of three important metrics – hop count, residual battery capacity, and average interface queue length taken together along with their associated weights. It helps to achieve load balancing and to extend the entire network lifetime. Simulation results show that the proposed load-balancing schemes significantly enhance the network performance in terms of average delay, packet delivery fraction and average residual battery capacity.
[...] gives the comparative study of various proposed algorithms for load balanced routing [ PROPOSED SCHEMES TO ACHIEVE LOAD BALANCING Most of the routing protocols in MANETs use hop count as a metric for path selection, due to which shortest route gets loaded heavily and results in route imbalance. Therefore, it is a requisite to provide a new routing metric in place of only hop count that can take also into account the node's current traffic and battery status/energy status while selecting the route. [...]
[...] In proposed strategies a load balanced routing path is selected among all feasible paths on the basis of weight value calculated for each path. The three parameters responsible for final route selection are - the average traffic queue, the route energy, and the hop count. Route selection is based on the weight value of each feasible path. The parameter weights may be fixed or adaptive to the network status depending upon the scheme. In a feasible path, the higher the weight value, the higher is its suitability for traffic distribution. [...]
[...] Initially when nodes have maximum energy α is high, route selection is mainly done on the basis of hop count and average traffic load as can be seen from eq As battery energy of nodes decreases with time, α decreases leading to more weight to the route energy parameter. Scheme 3 The scheme proposed next is almost similar to the one proposed above with a difference that intermediate nodes use the location information before broadcasting the RREQ packets further. Only the nodes that are closer to the destination with respect to the sources are allowed to broadcast RREQ packets further. [...]
[...] The results also show that the packet delivery fraction reduces with increase in load in the network Normalized routing load Fig shows normalized routing load. As expected, normalized routing load for first two proposed schemes is comparatively higher than AODV protocol. However, in the third proposed algorithm we try to restrict the broadcast of RREQ packets, which results in lower routing load in the network. Fig 5 verifies the same phenomenon. It has also been observed that normalized routing load increases with increase in number of sources in the network Average end-to-end delay Fig depicts the average end-to-end delay for variations of node's pause time. [...]
[...] Average Residual Battery Capacity: This metric depicts the amount of energy consumption of nodes with respect to time period Simulation Environment and Results Our simulation scenarios consists of 50 nodes moving at maximum velocity of 20m/s in a 600m x 600m grid area with a transmission range of 100m with 25 TCP flows. Each source node transmits packets at a rate of four packets per second, with a packet size of 1024 bytes. We run simulated for pause times of and 900 seconds. [...]
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