Weak state routing for large scale dynamic networks

Abstract

Routing in communication networks involves the indirection from a persistent name (or ID) to a locator and delivering packets based upon the locator. In a large-scale, highly dynamic network, the ID-to-locator mappings are both large in number, and change often. Traditional routing protocols require high overhead to keep these indirections up-to-date. In this paper, we propose Weak State Routing (WSR), a routing mechanism for large-scale highly dynamic networks. WSR's novelty is that it uses random directional walks biased occasionally by weak indirection state information in intermediate nodes. The indirection state information is weak, i.e. interpreted not as absolute truth, but as probabilistic hints. Nodes only have partial information about the region a destination node is likely to be. This method allows us to aggregate information about a number of remote locations in a geographic region. In other words, the state information maps a set-of-IDs to a geographical region. The intermediate nodes receiving the random walk use a method similar to longest-prefix-match in order to prioritize their mappings to decide how to bias and forward the random walk. WSR can also be viewed as an unstructured distributed hashing technique. WSR displays good rare-object recall with scalability properties similar to structured DHTs, albeit with more tolerance to dynamism and without constraining the degree distribution of the underlying network.Through simulations, we show that WSR offers a high packet delivery ratio, more than 98%. The control packet overhead incurred in the network scales as O(N ) for N -node networks. The number of mappings stored in the network appears to scale as Θ(N 3/2 ). We compare WSR with Dynamic Source Routing (DSR) and geographic forwarding (GPSR) combined with Grid Location Service (GLS). Our results indicate that WSR delivers more packets with less overhead at the cost of increased path length.

Weak State Routing for Large-Scale Dynamic Networks

“…Still, the paths are longer than the shortest paths, but the increase in the path length against the number of nodes has the same characteristics for all mobility models. We present the results for other performance criteria in the extended technical report [33] because of space constraints.…”

“…Since the cumulative distribution function (cdf) of a binomial random variable cannot be expressed in closed form, we cannot formulate the upper bound in , but numerical methods can be used to show that it is finite (see [33]). …”

Bloom Filter-Based Secure Data Forwarding in Large-Scale Cyber-Physical Systems

“…Bloom filters have also been used for information-guided routing [32][33][34], which adopt bloom filter-based probabilistic algorithms to locate the objects. Kumar et al introduce exponentially decaying bloom filter in [35], which is a representation of a set of objects of nodes.…”

Message-driven based energy-efficient routing in heterogeneous delay-tolerant networks

“…Owing to its large cost overhead, ER is considered to be energy inefficient. To this end, researchers have proposed several variants [12], [4], [3], [20] to limit the forwards.…”

“…The authors in [4] have proposed a probabilistic forwarding based routing approach that opportunistically forwards messages to the relay nodes that have maintained good encounter statistics with the forwarding node. In a similar probabilistic approach, the authors in [12] have used social similarity metrics among nodes to choose for their forwarding strategy, and in [3] the authors have used geometric distance among nodes in the forwarding strategy.…”