MANETs will play a critical role for communication in future battlefields. However, wireless communications, especially MANETs are susceptible to jamming. While MANETs will adapt to continuous jamming, intermittent jamming can disrupt the routing protocol. In the intermittent case, the network topology during non-jamming is generally quite different from the one during jamming. In the case of jamming by the enemy, one can use physical means to stop the jamming. However, in recent conflicts, jamming by friendly forces has been widely used. In this paper, we propose the jamming-aware routing protocols for the friendly jamming scenario where the jamming schedule (i.e., when jamming is to occur) is known to the friendly mobile nodes, but hidden from all enemy mobile nodes. The key idea is that the routing protocol freezes during jamming, whereas it resumes during non-jamming. This simple, but very effective, algorithm significantly improves the packet delivery ratio and other metrics compared to other routing protocols where the categories of the routing protocols considered are proactive and unicast with single-path or multipath. Finally, this paper concludes with a discussion on a routing protocol, which combines game-theoretic routing with jamming detection and probabilistic forwarding to avoid and overcome malicious jamming.

We propose a Context-aware Smallworld routing protocol for wireless ad-hoc networks which finds efficient routes to the destination nodes often through a very short chain of intermediate nodes, without using any routing table. This protocol exploits the “small-world” phenomenon of social networks where source-destination pairs typically get connected through few intermediate friends and the individuals can collectively discover such short paths. The key idea behind our routing protocol is that for forwarding an incoming packet to the destination, a node picks the next hop from among the one-hop neighbor from its one-hop neighborhood that is closest to the destination, and multiple randomly selected long-distance neighbor(s), i.e., from outside of its one-hop neighborhood, based on which of these neighbors is closest to the destination. The long-distance neighbors are selected by using their contextual information through a probabilistic mapping. We provide the theoretical foundations behind our protocol. This simple but effective algorithm can meet performance objectives for most scenarios by reducing loss and latency. Simulation results, using synthetic network topologies, have demonstrated that the routing performance of context-aware Smallworld is better than geographical (distance-based) Smallworld and other standard proactive routing protocols (e.g., OLSRv2) when metrics, such as packet losses, end-to-end delays, hop-counts, connectivity drops, and control traffic generated, are used as the key performance indicators. We also show that the proposed protocol is resilient to dynamic topology changes.

In wireless mesh networks, with the standard Optimized Link State Routing (OLSR) metric (i.e. hop count), traffic is routed on the shortest path without considering factors such as traffic distribution and link capacities. Consequently, some nodes may get overloaded from the uneven utilization of network resources. OLSR can be modified to use other link cost metrics, with route selection based on lowest cost path. With delay as the metric, OLSR reduces average round trip time but the load-aware routes may cause wide variance in delay and packet reordering due to route oscillations. We describe a new hybrid routing approach that combines the strength of a) link state routing (e.g. fast convergence), b) load-aware routing (e.g., avoiding congested paths) and c) cognitive routing (e.g. learning to avoid path oscillations). In particular, we investigate the use of Q-learning with OLSR to increase network capacity and reduce congestion delay. We present simulation results for a 36 node dynamic mobile ad hoc network, with standard OLSR, a non-cognitive load-aware OLSR (OLSR-D) and our new hybrid cognitive load-aware OLSR (OLSR-Q). We show that OLSR-Q >; OLSR-D >; OLSR in terms of reducing delay and increasing network capacity. Furthermore, we show that, unlike conventional cognitive Q-routing protocols, our hybrid approach does not reduce performance at low load. Although OLSR-Q can significantly reduce delay and improve capacity, the learning time can reduce connectivity and the distribution of more link state information can reduce raw link capacity. We show how adding OLSR, OLSR-D and OLSR-Q as routing options into the Cognitive Network Engineering Design Analytic Toolset (C-NEDAT), we can select the best routing protocol and parameters (e.g., learning rate) for a given network and its mission. We verify simulation performance improvements by implementing the OLSR-Q in on a 9 node wireless testbed.

The mobile IP (MIP) protocol for IP version 4 provides continuous Internet connectivity to mobile hosts. However, currently it has some drawbacks in the areas of survivability, performance, interoperability with protocols for providing QoS. We have proposed an alternative protocol, mobile IP with location registers (MIP-LR), which overcomes some of these drawbacks and is closer to the "service node" database approach used in the public switched telephone network (PSTN): before launching a packet to the mobile host, the sender first queries a database, called the home location register (HLR), to obtain the recipient's current location. MIP-LR is designed for operation in enterprise environments or within logical administrative domains. We focus on showing how MIP-LR enhances the survivability of MIP by eliminating some of the functions which MIP introduces for mobility support, allowing the HLR to be placed outside the mobile's home network in case the latter is particularly vulnerable, and replicating and distributing HLRs. We present two schemes for managing the multiple HLRs and enabling mobile and correspondent hosts to dynamically discover the addresses of the HLRs serving a given mobile host. The first scheme introduces a set of translation server (TS) databases while the second uses a form of quorum consensus based on the triangle lattice (TL); for the latter we present an enhanced protocol called the optimistic TL(OTL). For both schemes we present algorithms for mobile host registration and packet delivery, protocols for recovery from HLR failures, and complexity analysis of the overhead involved.