Abstract-This paper presents a routing algorithm for computer network using mobile agents (Ant algorithm) and genetic algorithm. Ant algorithm is a class of Swarm Intelligence (SI) algorithms. SI is the local interaction of many simple agents to achieve a global goal. SI is based on social insect metaphor for solving different types of problems. Ant algorithm uses mobile agents called ants to explore network. Ants help in finding paths between two nodes in the network. Paths generated by ants act as input to Genetic Algorithm (GA). GA finds the set of suboptimal paths between nodes with the objective of minimum cost. This hybrid algorithm exhibits better performance when compared to basic ant algorithm.
Currently, there is very little research that aims at Taking all this into consideration, existing infrastructure handling QoS requirements using multipath routing in a very should be monitored for both energy and communication. energy constrained environment like sensor networks. In this paper, Energy efficient fault-tolerant multipath routing Communication between nodes is a major consumer of technique which utilizes multiple paths between source and the energy in sensor networks, which makes distributed sink. has been proposed. This protocol is intended to provide a processing capability to be an important constraint for sensor reliable transmission environment with low energy consumption, network. A centralized system leads to more energy depletion, by efficiently utilizing the energy availability and the available as some of the sensors needs to communicate over long bandwidth of the nodes to identify multiple routes to the distances and it also include more number of bits to be destination. To achieve reliability and fault tolerance, this transmitted. Processing as much information as achievable in protocol selects reliable paths based on the average reliability the neighborhood would be an excellent thought as this rank (ARR) of the paths. Average reliability rank of a path is reduces the total quantity of bits broadcasted. based on each node's reliability rank (RR), which represents the probability that a node correctly delivers data to the destination.Sensor networks are employed by various applications, forIn case the existing route encounters some unexpected link or instance: Environmental monitoring is an application, in route failure, the algorithm selects the path with the next highest which monitoring of air, soil and water, condition based ARR, from the list of selected paths. Simulation results show that maintenance is dealt with. Habitat monitoring is another the proposed protocol minimizes the energy and latency and application, in which the plant and animal species population maximizes the delivery ratio. and behavior are determined. It is worthy to mention seismic detection, military surveillance, inventory tracking, smart
In case of wireless routing in sensor networks, data aggregation has been proposed as a predominantly constructive prototype. Most of the routing algorithms for traditional networks are address centric, and the ad hoc nature of wireless sensor network makes them unsuitable for practical applications. Data-centric technologies that carry out in-network aggregation of data to capitulate energyefficient dissemination are essential. In this paper, we propose a Pull based Energy Efficient Data Aggregation (PEEDA) approach, to effectively deliver the data to the sink. In this approach, the sink will broadcast an interest message containing its required data model, to all the nodes. We form an cost effective aggregation tree towards the sink based on the ToD structure. When the aggregator receives the data from the sources, it aggregates the data depending on the interest message using spatial and temporal convergence. To achieve energy efficient aggregation, the MAC protocol uses the partially overlapped channels. By simulation results, we show that the proposed scheme consumes less energy and reduces the overhead and delay.
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