We develop an on-demand, multipath distance vector protocol for mobile ad hoc networks. Specifically, we propose multipath extensions to a well-studied single path routing protocol known as Ad hoc On-demand Distance Vector (AODV). The resulting protocol is referred to as Ad hoc Ondemand Multipath Distance Vector (AOMDV). The protocol computes multiple loop-free and link-disjoint paths. Loopfreedom is guaranteed by using a notion of "advertised hopcount." Link-disjointness of multiple paths is achieved by using a particular property of flooding. Performance comparison of AOMDV with AODV using ns-2 simulations shows that AOMDV is able to achieve a remarkable improvement in the end-to-end delay --- often more than a factor of two, and is also able to reduce routing overheads by about 20%. 1

Abstract. Multipath on-demand routing protocols for mobile ad hoc networks try to reduce control overhead and end-to-end delay by computing multiple paths with a single route discovery process. We propose Graph-based Multipath Routing (GMR), a novel multipath routing protocol that generate the network topology graph to compute all link disjoint paths in the network. The destination node computes link disjoint paths using the local graph search algorithm. We present our simulation results compared with DSR and Multipath DSR 1

Abstract—One of the key issues in the study of multiple route protocols in mobile ad hoc networks (MANETs) is how to select routes to the packet transmission destination. There are currently two route selection methods: primary routing policy and load-balancing policy. Many ad hoc routing protocols are based on primary (fastest or shortest but busiest) routing policy from the self-standpoint of traffic transmission optimization of each node. Load-balancing protocols equalize transmission load among multiple routes in the network. However, the lack of global perspective can cause congestion in primary policy and prolong delay time in load-balancing policy. So, although they are sometimes efficient, these two types of policies cannot adapt to intricately changing network conditions. We propose a new multiple route protocol with an Adaptive route selection Policy based on a Back propagation Neural network (APBN) to optimize selection policy. In our study, we used a gradient ascent algorithm to determine the relationship between different optimum route selection polices and varying conditions in the communication network and to make a neural network that learns this relationship using the Back Propagation (BP) algorithm to predict the next optimum route selection policy. We evaluated our protocol using Omnet simulator. The results show that the proposed scheme performs better than current protocols. Index Terms—mobile ad hoc network, multiple route, back propagation, neural network, gradient ascent algorithm I.

Abstract — In a typical mobile ad hoc network, mobile computing devices wander autonomously and communicate via temporary links in a self-organized computing system without any central administrator or infrastructure support. To support truly ad hoc impromptu communication among such uncoordinated devices, a data multipath routing algorithm can be used because there is no need to rely on a centralized encryption facility (e.g., a PKI server) or complicated distributed keying protocols. In this paper, we propose a data multipath routing algorithm called Multipath TCP Security (MTS) to enhance the data security. In MTS, the source node adaptively chooses the available routes rather than exhaustively testing the “stored routes” one by one. Simulation results show that our algorithm provides a reasonably good level of security and performance. Index Terms — TCP, wireless security, ad hoc networks, multipath routing, interception rates. I.

Current trends in computing include increases in both distribution and wireless connectivity, leading to highly dynamic, complex environments on top of which applications must be built.

Abstract—Opportunistic routing [2], [3] has been shown to improve the network throughput, by allowing nodes that overhear the transmission and closer to the destination to participate in forwarding packets, i.e., in forwarder list. The nodes in forwarder list are prioritized and the lower priority forwarder will discard the packet if the packet has been forwarded by a higher priority forwarder. One challenging problem is to select and prioritize forwarder list such that a certain network performance is optimized. In this paper, we focus on selecting and prioritizing forwarder list to minimize energy consumption by all nodes. We study both cases where the transmission power of each node is fixed or dynamically adjustable. We present an energy-efficient opportunistic routing strategy, denoted as EEOR. Our extensive simulations in TOSSIM show that our protocol EEOR performs better than the well-known ExOR protocol (when adapted in sensor networks) in terms of the energy consumption, the packet loss ratio, and the average delivery delay. Index Terms—Sensor networks, opportunistic routing, energy. Ç 1