Optimizing Clustering Algorithm In Mobile Ad Hoc Networks Using Simulated Annealing

In this paper, we demonstrate how simulated annealing algorithm can be applied to clustering algorithms used in ad hoc networks; specifically our recently proposed weighted clustering algorithm (WCA) is optimized by simulated annealing. As the simulated annealing stands to be a powerful stochastic search method, its usage for combinatorial optimization problems was found to be applicable in our problem domain. The problem formulation along with the parameters is mapped to be an individual solution as an input to the simulated annealing algorithm. Input consists of a random set of clusterhead set along with its members and the set of all possible dominant sets chosen from a given network of N nodes as obtained from the original WCA. Simulated annealing uses this information to find the best solution defined by computing the objective function and obtaining the best fitness value. The proposed technique is such that each clusterhead handles the maximum possible number of mobile nodes in its cluster in order to facilitate the optimal operation of the MAC protocol. Consequently, it results in the minimum number of clusters and hence clusterheads. Simulation results exhibit improved performance of the optimized WCA than the original WCA

Balancing Loads In Mobile Ad Hoc Networks

Mobile ad hoc network consists of freely moving nodes communicating with each other through wireless links. In this paper, we propose a load balancing algorithm for these networks with nodes having different processing powers and thus can perform extensive computations apart from forwarding packets for other nodes. These nodes will also have various degrees of battery powers as well. Due to the heterogeneity of the systems in terms of processing and battery powers, naturally, there will be load imbalance. If the workload is distributed among the nodes in the system based on the resources of individual nodes, the average execution time can be minimized and the lifetime of the nodes can be maximized. Our proposed load balancing algorithm takes into consideration several realistic parameters such as processing and batter powers of each node, and communication cost for the loads being transferred between the overloaded and underloaded nodes. Simulation experiments demonstrate that our proposed algorithm achieves performance improvements in terms of processor utilization, execution time, and balance factor

Scenario-Based Performance Analysis Of Mac Protocols For Wireless Sensor Networks

Due to inherent resources constraints of the sensor nodes, new algorithms have to be designed and tailored to accommodate the specific needs of the wireless sensor networks. The energy consumption is perhaps the biggest concern since the sensor nodes have limited power sources. There are two major approaches to minimize the communication overhead. The first approach is at the MAC and networking layers and the second one is the data reduction through data aggregation. In this paper, we compare IEEE 802.11 standard, S-MAC, TDMA-based protocol with three different scenarios in terms of energy consumption. Packets received at the sink node parameter have been simulated with the first two scenarios. All the nodes including the sink node is static in the first scenario. The sources are mobile and can either move towards or away from the static sink in the second scenario. The sources and the sink move in a random motion in the last scenario