We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of routers and a packet's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only information about a router's immediate neighbors in the network topology. When a packet reaches a region where greedy forwarding is impossible, the algorithm recovers by routing around the perimeter of the region. By keeping state only about the local topology, GPSR scales better in per-router state than shortest-path and ad-hoc routing protocols as the number of network destinations increases. Under mobility's frequent topology changes, GPSR can use local topology information to find correct new routes quickly. We describe the GPSR protocol, and use extensive simulation of mobile wireless networks to compare its performance with that of Dynamic Source Routing. Our simulations demonstrate GPSR's scalability on densely deployed wireless networks.

/pdf/gpsr-greedy-perimeter-stateless-routing-for-wireless-59gz21qf8y.pdf

GPSR: greedy perimeter stateless routing for wireless networks

https://www.cs.montana.edu/courses/csci566/Ref/CR-Survey.pdf

NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey

Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm for such coordination. Directed diffusion is datacentric in that all communication is for named data. All nodes in a directed diffusion-based network are application-aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network. We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network.

/pdf/directed-diffusion-a-scalable-and-robust-communication-4tsx5vxsas.pdf

Directed diffusion: a scalable and robust communication paradigm for sensor networks

"A Survey of Mobility Models for Ad Hoc Network Research," Wireless Comm. & Mobile Computing (WCMC) : Special issue on Mobile Ad Hoc Networking : Research

In the performance evaluation of a protocol for an ad hoc network, the protocol should be tested under realistic conditions including, but not limited to, a sensible transmission range, limited buffer space for the storage of messages, representative data traffic models, and realistic movements of the mobile users (i.e., a mobility model). This paper is a survey of mobility models that are used in the simulations of ad hoc networks. We describe several mobility models that represent mobile nodes whose movements are independent of each other (i.e., entity mobility models) and several mobility models that represent mobile nodes whose movements are dependent on each other (i.e., group mobility models). The goal of this paper is to present a number of mobility models in order to offer researchers more informed choices when they are deciding upon a mobility model to use in their performance evaluations. Lastly, we present simulation results that illustrate the importance of choosing a mobility model in the simulation of an ad hoc network protocol. Specifically, we illustrate how the performance results of an ad hoc network protocol drastically change as a result of changing the mobility model simulated.

/pdf/a-survey-of-mobility-models-for-ad-hoc-network-research-ygkxat400x.pdf

A survey of mobility models for ad hoc network research

We consider Byzantine consensus in a synchronous system where nodes are connected by a network modeled as a directed graph, i.e., communication links between neighboring nodes are not necessarily bi-directional. The directed graph model is motivated by wireless networks wherein asymmetric communication links can occur. In the classical point-to-point communication model, a message sent on a communication link is private between the two nodes on the link. This allows a Byzantine faulty node to equivocate, i.e., send inconsistent information to its neighbors. This paper considers the local broadcast model of communication, wherein transmission by a node is received identically by all of its outgoing neighbors. This allows such neighbors to detect a faulty node's attempt to equivocate, effectively depriving the faulty nodes of the ability to send conflicting information to different neighbors. 
Prior work has obtained sufficient and necessary conditions on undirected graphs to be able to achieve Byzantine consensus under the local broadcast model. In this paper, we obtain tight conditions on directed graphs to be able to achieve Byzantine consensus with binary inputs under the local broadcast model. The results obtained in the paper provide insights into the trade-off between directionality of communication and the ability to achieve consensus.

Exact Byzantine Consensus on Arbitrary Directed Graphs Under Local Broadcast Model.

We study the problem of multi-agent optimization in the presence of communication failures, where agents are connected by a strongly connected communication network. Specifically, we are interested in optimizing $h(x)=\frac{1}{n}\sum_{i=1}^n h_i(x)$, where $\mathcal{V}=\{1, \ldots, n\}$ is the set of agents, and $h_i(\cdot)$ is agent $i$'s local cost function. We consider the scenario where the communication links may suffer packet-dropping failures (i.e., the sent messages are not guaranteed to be delivered in the same iteration), but each link is reliable at least once in every $B$ consecutive message transmissions. This bounded time reliability assumption is reasonable since it has been shown that with unbounded message delays, convergence is not guaranteed for reaching consensus -- a special case of the optimization problem of interest. We propose a robust distributed optimization algorithm wherein each agent updates its local estimate using slightly different routines in odd and even iterations. We show that these local estimates converge to a common optimum of $h(\cdot)$ sub-linearly at convergence rate $O(\frac{1}{\sqrt{t}})$, where $t$ is the number of iteration. Our proposed algorithm combines the Push-Sum Distributed Dual Averaging method with a robust average consensus algorithm. The main analysis challenges come from the fact that the effective communication network is time varying, and that each agent does not know the actual number of reliable outgoing links at each iteration.

Robust Multi-Agent Optimization: Coping with Packet-Dropping Link Failures.

This paper addresses a distributed throughput- optimal CSMA for wireless networks, which is called the preemptive CSMA. Distinguished from other throughput-optimal CSMAs in the literature, it achieves the optimality even with the throughput loss caused by discrete backoff time, non-zero carrier sense delay and data packet collisions. Moreover, the analysis on the preemptive CSMA provides the understanding on the relationship among the throughput-optimal CSMAs.

A Distributed Throughput-Optimal CSMA with Data Packet Collisions

We present a distributed optimization protocol that preserves statistical privacy of agents’ local cost functions against a passive adversary that corrupts some agents in the network. The protocol is a composition of a distributed “ zero-sum ” obfuscation protocol that obfuscates the agents’ local cost functions, and a standard non-private distributed optimization method. We show that our protocol protects the statistical privacy of the agents’ local cost functions against a passive adversary that corrupts up to $t$ arbitrary agents as long as the communication network has ( $t+1$ )-vertex connectivity. The “ zero-sum ” obfuscation protocol preserves the sum of the agents’ local cost functions and therefore ensures accuracy of the computed solution.

Preserving Statistical Privacy in Distributed Optimization

This work considers a point-to-point network of n nodes connected by directed links, and proves tight necessary and sufficient conditions on the underlying communication graphs for achieving consensus among these nodes under crash faults. We identify the conditions in both synchronous and asynchronous systems

Nitin H. Vaidya

Papers

Exact Byzantine Consensus on Arbitrary Directed Graphs Under Local Broadcast Model.

Robust Multi-Agent Optimization: Coping with Packet-Dropping Link Failures.

A Distributed Throughput-Optimal CSMA with Data Packet Collisions

Preserving Statistical Privacy in Distributed Optimization

Crash-Tolerant Consensus in Directed Graphs.