EEGRA: Energy Efficient Geographic Routing Algorithms for Wireless Sensor Network

[[abstract]]Energy efficiency is critical in wireless sensor networks (WSN) for system reliability and deployment cost. The power consumption of the communication in multi-hop WSN is primarily decided by three factors: routing distance, signal interference, and computation cost of routing. Several routing algorithms designed for energy efficiency or interference avoidance had been proposed. However, they are either too complex to be useful in practices or specialized for certain WSN architectures. In this paper, we propose two energy efficient geographic routing algorithms (EEGRA) for wireless sensor networks, which are based on existing geographic routing algorithms and take all three factors into account. The first algorithm combines the interference into the routing cost function, and uses it in the routing decision. The second algorithm transforms the problem into a constrained optimization problem, and solves it by searching the optimal discretized interference level. We integrate four geographic routing algorithms: GOAFR+, Face Routing, GPSR, and RandHT, to both EEGRA algorithms and compare them with three other routing methods in terms of power consumption and computation cost for the grid and irregular sensor topologies. The results of our experiments show both algorithms conserve sensor’s routing energy 30% ~ 50% comparing to general geographic routing algorithms. In addition, the time complexity of EEGRA algorithms is similar to the geographic greedy routing methods, which is much faster than the optimal SINR-based algorithm.[[conferencetype]]國際[[conferencedate]]20121213~20121215[[iscallforpapers]]Y[[conferencelocation]]San Marcos, Texas, US

A reduced-uncertainty hybrid evolutionary algorithm for solving dynamic shortest-path routing problem

The need for effective packet transmission to deliver advanced performance in wireless networks creates the need to find shortest network paths efficiently and quickly. This paper addresses a Reduced Uncertainty Based Hybrid Evolutionary Algorithm (RUBHEA) to solve Dynamic Shortest Path Routing Problem (DSPRP) effectively and rapidly. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are integrated as a hybrid algorithm to find the best solution within the search space of dynamically changing networks. Both GA and PSO share context of individuals to reduce uncertainty in RUBHEA. Various regions of search space are explored and learned by RUBHEA. By employing a modified priority encoding method, each individual in both GA and PSO are represented as a potential solution for DSPRP. A Complete statistical analysis has been performed to compare the performance of RUBHEA with various state-of-the-art algorithms. It shows that RUBHEA is considerably superior (reducing the failure rate by up to 50%) to similar approaches with increasing number of nodes encountered in the networks

Resilient routing in the internet

Although it is widely known that the Internet is not prone to random failures, unplanned failures due to attacks can be very damaging. This prevents many organisations from deploying beneficial operations through the Internet. In general, the data is delivered from a source to a destination via a series of routers (i.e routing path). These routers employ routing protocols to compute best paths based on routing information they possess. However, when a failure occurs, the routers must re-construct their routing tables, which may take several seconds to complete. Evidently, most losses occur during this period. IP Fast Re-Route (IPFRR), Multi-Topology (MT) routing, and overlays are examples of solutions proposed to handle network failures. These techniques alleviate the packet losses to different extents, yet none have provided optimal solutions. This thesis focuses on identifying the fundamental routing problem due to convergence process. It describes the mechanisms of each existing technique as well as its pros and cons. Furthermore, it presents new techniques for fast re-routing as follows. Enhanced Loop-Free Alternates (E-LFAs) increase the repair coverage of the existing techniques, Loop-Free Alternates (LFAs). In addition, two techniques namely, Full Fast Failure Recovery (F3R) and fast re-route using Alternate Next Hop Counters (ANHC), offer full protection against any single link failures. Nevertheless, the former technique requires significantly higher computational overheads and incurs longer backup routes. Both techniques are proved to be complete and correct while ANHC neither requires any major modifications to the traditional routing paradigm nor incurs significant overheads. Furthermore, in the presence of failures, ANHC does not jeopardise other operable parts of the network. As emerging applications require higher reliability, multiple failures scenarios cannot be ignored. Most existing fast re-route techniques are able to handle only single or dual failures cases. This thesis provides an insight on a novel approach known as Packet Re-cycling (PR), which is capable of handling any number of failures in an oriented network. That is, packets can be forwarded successfully as long as a path between a source and a destination is available. Since the Internet-based services and applications continue to advance, improving the network resilience will be a challenging research topic for the decades to come