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 study the problem of constrained distributed optimization in multi-agent networks when some of the computing agents may be faulty. In this problem, the system goal is to have all the non-faulty agents collectively minimize a global objective given by weighted average of local cost functions, each of which is initially known to a non-faulty agent only. In particular, we are interested in the scenario when the computing agents are connected by an arbitrary directed communication network, some of the agents may suffer from crash faults or Byzantine faults, and the estimate of each agent is restricted to lie in a common constraint set. This problem finds its applications in social computing and distributed large-scale machine learning. 
The fault-tolerant multi-agent optimization problem was first formulated by Su and Vaidya, and is solved when the local functions are defined over the whole real line, and the networks are fully-connected. In this report, we consider arbitrary directed communication networks and focus on the scenario where, local estimates at the non-faulty agents are constrained, and only local communication and minimal memory carried across iterations are allowed. In particular, we generalize our previous results on fully-connected networks and unconstrained optimization to arbitrary directed networks and constrained optimization. As a byproduct, we provide a matrix representation for iterative approximate crash consensus. The matrix representation allows us to characterize the convergence rate for crash iterative consensus.

Fault-Tolerant Distributed Optimization (Part IV): Constrained Optimization with Arbitrary Directed Networks.

Multicasting can be an useful service in wireless mesh networks (WMNs), which have gained significant acceptance in recent years due to their potentials of providing a low-cost wireless backhaul service to mobile clients. Many applications in WMNs require efficient and reliable multicast communication, i.e., with high delivery ratio but with less overhead, among a group of recipients. However, in spite of its significance, there has been little work on providing such a multicast service in multi-channel mesh networks. Traditional multicasting protocols for wireless multi-hop networks mostly assume that all nodes (equipped with a single interface) collaborate on the same channel. The single-channel assumption is not always true for WMNs that often provide the nodes with multiple interfaces for the purpose of substantial performance enhancement. In multi-channel/interface mesh environments, the same multicast data needs to be sent multiple times by a sender node if its neighboring nodes operate on different channels. In this paper, we try to tackle this challenging issue of how to design a multicast protocol more suitable for multi-interface and multi-channel WMNs. Our multicasting protocol builds multicast paths while inviting multicast members, and allocates the same channel to each of neighboring members in a bottom up manner. This mechanism can reduce message overheads and delivery delays while guaranteeing successful message deliveries. For the performance evaluation, we have implemented the proposed scheme on a multi-channel/interface mesh network test-bed with two IEEE 802.11a cards per node.

Efficient multicasting for multi-channel multi-interface wireless mesh networks

In recent years, fair scheduling and quality of service (QoS) in wireless LAN have received significant attention from the networking research community. This paper presents a distributed protocol for priority and fair scheduling in a wireless LAN. The proposed protocol supports multiple priorities, as well as a mechanism (using weights) for controlling the way bandwidth is shared by flows within a given priority level.

Priority and fair scheduling in a wireless LAN

Adaptively changing weights for fair scheduling in broadcast environments is disclosed. In one embodiment, a computer-implemented method for allocating bandwidth among a plurality of flows, such as nodes, sharing an output link, such as a network, is disclosed. The method includes adaptively determining a weight for each flow, based on a predetermined criteria, and allocating a portion of bandwidth to each flow proportionally to the weight for the flow. In one embodiment, the predetermined criteria takes into account an input rate of data packets for each flow, while in another embodiment, the predetermined criteria takes into account an queue size for each flow.

Adaptively changing weights for fair scheduling in broadcast environments

The CAP theorem is a fundamental result that applies to distributed storage systems. In this paper, we first present and prove two CAP-like impossibility theorems. To state these theorems, we present probabilistic models to characterize the three important elements of the CAP theorem: consistency (C), availability or latency (A), and partition tolerance (P). The theorems show the un-achievable envelope, i.e., which combinations of the parameters of the three models make them impossible to achieve together. Next, we present the design of a class of systems called PCAP that perform close to the envelope described by our theorems. In addition, these systems allow applications running on a single data-center to specify either a latency SLA or a consistency SLA. The PCAP systems automatically adapt, in real-time and under changing network conditions, to meet the SLA while optimizing the other C/A metric. We incorporate PCAP into two popular key-value stores -- Apache Cassandra and Riak. Our experiments with these two deployments, under realistic workloads, reveal that the PCAP system satisfactorily meets SLAs, and performs close to the achievable envelope. We also extend PCAP from a single data-center to multiple geo-distributed data-centers.

Nitin H. Vaidya

Papers

Fault-Tolerant Distributed Optimization (Part IV): Constrained Optimization with Arbitrary Directed Networks.

Efficient multicasting for multi-channel multi-interface wireless mesh networks

Priority and fair scheduling in a wireless LAN

Adaptively changing weights for fair scheduling in broadcast environments

Characterizing and Adapting the Consistency-Latency Tradeoff in Distributed Key-value Stores