In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation), that efficiently disseminates information among sensors in an energy-constrained wireless sensor network. Nodes running a SPIN communication protocol name their data using high-level data descriptors, called meta-data. They use meta-data negotiations to eliminate the transmission of redundant data throughout the network. In addition, SPIN nodes can base their communication decisions both upon application-specific knowledge of the data and upon knowledge of the resources that are available to them. This allows the sensors to efficiently distribute data given a limited energy supply. We simulate and analyze the performance of two specific SPIN protocols, comparing them to other possible approaches and a theoretically optimal protocol. We find that the SPIN protocols can deliver 60% more data for a given amount of energy than conventional approaches. We also find that, in terms of dissemination rate and energy usage, the SPlN protocols perform close to the theoretical optimum.

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Adaptive protocols for information dissemination in wireless sensor networks

In the Hamadryas baboon, males are substantially larger than females. A troop of baboons is subdivided into a number of ‘one-male groups’, consisting of one adult male and one or more females with their young. The male prevents any of ‘his’ females from moving too far from him. Kummer (1971) performed the following experiment. Two males, A and B, previously unknown to each other, were placed in a large enclosure. Male A was free to move about the enclosure, but male B was shut in a small cage, from which he could observe A but not interfere. A female, unknown to both males, was then placed in the enclosure. Within 20 minutes male A had persuaded the female to accept his ownership. Male B was then released into the open enclosure. Instead of challenging male A , B avoided any contact, accepting A’s ownership.

Evolution and the Theory of Games

Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption (which is essential to extend the network operational time) and radio interference (with a positive effect on the network traffic carrying capacity). The goal of this technique is to control the topology of the graph representing the communication links between network nodes with the purpose of maintaining some global graph property (e.g., connectivity), while reducing energy consumption and/or interference that are strictly related to the nodes' transmitting range. In this article, we state several problems related to topology control in wireless ad hoc and sensor networks, and we survey state-of-the-art solutions which have been proposed to tackle them. We also outline several directions for further research which we hope will motivate researchers to undertake additional studies in this field.

/pdf/topology-control-in-wireless-ad-hoc-and-sensor-networks-3e17u396zt.pdf

Topology Control in Wireless Ad Hoc and Sensor Networks

In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation), that efficiently disseminate information among sensors in an energy-constrained wireless sensor network. Nodes running a SPIN communication protocol name their data using high-level data descriptors, called meta-data. They use meta-data negotiations to eliminate the transmission of redundant data throughout the network. In addition, SPIN nodes can base their communication decisions both upon application-specific knowledge of the data and upon knowledge of the resources that are available to them. This allows the sensors to efficiently distribute data given a limited energy supply. We simulate and analyze the performance of four specific SPIN protocols: SPIN-PP and SPIN-EC, which are optimized for a point-to-point network, and SPIN-BC and SPIN-RL, which are optimized for a broadcast network. Comparing the SPIN protocols to other possible approaches, we find that the SPIN protocols can deliver 60% more data for a given amount of energy than conventional approaches in a point-to-point network and 80% more data for a given amount of energy in a broadcast network. We also find that, in terms of dissemination rate and energy usage, the SPIN protocols perform close to the theoretical optimum in both point-to-point and broadcast networks.

/pdf/negotiation-based-protocols-for-disseminating-information-in-1i6jhgr0p8.pdf

Negotiation-based protocols for disseminating information in wireless sensor networks

This self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation. The unifying theme is a formal model for robotic networks that explicitly incorporates their communication, sensing, control, and processing capabilities--a model that in turn leads to a common formal language to describe and analyze coordination algorithms.Written for first- and second-year graduate students in control and robotics, the book will also be useful to researchers in control theory, robotics, distributed algorithms, and automata theory. The book provides explanations of the basic concepts and main results, as well as numerous examples and exercises.Self-contained exposition of graph-theoretic concepts, distributed algorithms, and complexity measures for processor networks with fixed interconnection topology and for robotic networks with position-dependent interconnection topology Detailed treatment of averaging and consensus algorithms interpreted as linear iterations on synchronous networks Introduction of geometric notions such as partitions, proximity graphs, and multicenter functions Detailed treatment of motion coordination algorithms for deployment, rendezvous, connectivity maintenance, and boundary estimation

/pdf/distributed-control-of-robotic-networks-a-mathematical-1q6nfcvi2l.pdf

Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms

Two mobile agents, starting from different nodes of a network at possibly different times, have to meet at the same node. This problem is known as rendezvous. Agents move in synchronous rounds using a deterministic algorithm. In each round, an agent decides to either remain idle or to move to one of the adjacent nodes. Each agent has a distinct integer label from the set {1,...,L}, which it can use in the execution of the algorithm, but it does not know the label of the other agent.Two main efficiency measures of a rendezvous algorithm's performance are its time (the number of rounds until the meeting) and its cost (the combined number of edge traversals by both agents). We investigate tradeoffs between these two measures. A natural benchmark for both time and cost of rendezvous in a network is the number of edge traversals needed for visiting all nodes of the network, called the exploration time. Indeed, this is a lower bound on both the time and the cost of rendezvous. Hence we express the time and cost of rendezvous as functions of an upper bound E on the time of exploration (known to both agents) and the size L of the label space. We present two natural rendezvous algorithms. Algorithm Cheap has cost O(E) (and, in fact, a version of this algorithm for the model where the agents start simultaneously has cost exactly E) and time O(EL). Algorithm Fast has both time and cost O(E log L). Our main contributions are lower bounds showing that, perhaps surprisingly, these two algorithms capture the tradeoffs between time and cost of rendezvous almost tightly. We show that any rendezvous algorithm of cost asymptotically E (i.e., of cost E+o(E)) must have time Ω(EL). On the other hand, we show that any rendezvous algorithm with time complexity O(E log L) must have cost Ω (E log L). Moreover, while our algorithms work for arbitrary connected graphs and arbitrary starting times of the agents, these lower bounds hold even in a scenario that is very favorable for potential rendezvous algorithms, i.e., for oriented rings of known size and with simultaneous start.

Time versus cost tradeoffs for deterministic rendezvous in networks

We consider the problem of disseminating messages in networks. We are interested in information dissemination algorithms in which machines operate independently without any knowledge of the network topology or size. Three communication tasks of increasing difficulty are studied. In blind broadcasting (BB), the goal is to communicate the source message to all nodes. In acknowledged blind broadcasting (ABB), the goal is to achieve BB and inform the source about it. Finally, in full synchronization (FS), all nodes must simultaneously enter the state terminated after receiving the source message. The algorithms should be efficient both in terms of the time required and the communication overhead they put on the network. We limit the latter by allowing every node to send a message to at most one neighbor in each round. We show that BB is achieved in time at most 2n in any n-node network and show networks in which time 2n − o(n) is needed. For ABB, we show algorithms working in time (2 + ϵ)n, for any fixed positive constant ϵ and sufficiently large n. Thus, for both BB and ABB, our algorithms are close to optimal. Finally, we show a simple algorithm for FS working in time 3n and a more complicated algorithm which works in time 2.9n. The optimal time of full synchronization remains an open problem. © 2001 John Wiley & Sons, Inc.

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Efficient communication in unknown networks

https://hal.archives-ouvertes.fr/hal-00341600/document

Impact of memory size on graph exploration capability

In broadcasting, information originally held in one node of a communication network (called the source) has to be transmitted to all other nodes. In a unit of time, every node which already received the source message can transmit it to one neighbor. In classical broadcasting, the choice of neighbors to be informed by a node and the order in which they are informed may depend on the source. Thus, nodes need to store many transmission lists corresponding to different possible sources and need to know the source to adapt their behavior accordingly. In this paper, we consider a variant of broadcasting in which every node is given a priori a single ordered list containing some of its neighbors. This list is meant to be universal for all possible sources. Upon obtaining the source message, a node transmits it to the neighbors from its list in prescribed order and then stops. This requires substantially less local memory devoted to schedule communication but usually increases broadcasting time. We compare broadcasting time in this and in the classical model and design optimal broadcasting schemes in the universal-list model for trees, rings, and grids. For tori and for complete graphs, we give upper bounds on broadcasting time.

Broadcasting with universal lists

Message transmission in ATM networks is via virtual paths. Packets are routed along virtual paths by maintaining a routing field whose subfields determine the intermediate destinations of the packet. In such a network it is important to construct path layouts that minimize the hop number (i.e. the number of virtual paths used to travel between any two nodes) as a function of edge-congestion (i.e. the number of virtual paths passing through a link). In this paper we construct asymptotically optimal virtual path layouts for chains and meshes.

Andrzej Pelc

Papers

Time versus cost tradeoffs for deterministic rendezvous in networks

Efficient communication in unknown networks

Impact of memory size on graph exploration capability

Broadcasting with universal lists

Hop-Congestion Trade-Offs for High-Speed Networks