An O(log n) dominating set protocol for wireless ad-hoc networks under the physical interference model

Scheideler, Christian; Richa, Andréa W.; Santi, Paolo

doi:10.1145/1374618.1374632

Cited by 101 publications

(82 citation statements)

References 31 publications

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“…The resulting leader backbone forms a connected dominating set (CDS). The use of a CDS in radio networks is a common strategy; c.f., [12,30,31,35,38]. Unlike this existing work, however, our task is simplified by both the availability of location information and the lack of need to deal explicitly with contention on the channel.…”

Section: The Leader Election Problemmentioning

confidence: 99%

The abstract MAC layer

Kühn

Lynch²,

Newport³

2010

Distrib. Comput.

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A diversity of possible communication assumptions complicates the study of algorithms and lower bounds for radio networks. We address this problem by defining an abstract MAC layer. This service provides reliable local broadcast communication, with timing guarantees stated in terms of a collection of abstract delay functions applied to the relevant contention. Algorithm designers can analyze their algorithms in terms of these functions, independently of specific channel behavior. Concrete implementations of the abstract MAC layer over basic radio network models generate concrete definitions for these delay functions, automatically adapting bounds proven for the abstract service to bounds for the specific radio network under consideration. To illustrate this approach, we use the abstract MAC layer to study the new problem of Multi-Message Broadcast, a generalization of standard single-message broadcast in which multiple messages can originate at different times and locations in the network. We present and analyze two algorithms for Multi-Message Broadcast in static networks: a simple greedy algorithm and one that uses regional leaders. We then indicate how these results can be extended to mobile networks.

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Section: The Leader Election Problemmentioning

confidence: 99%

The abstract MAC layer

Kühn

Lynch²,

Newport³

2010

Distrib. Comput.

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“…Yet, recent works [14,24] support the conjecture that the same asymptotic result on the value of k holds also in a cost-based connection model, which is shown in [24] to closely resemble lognormal shadowing propagation (i.e., irregular coverage regions).…”

Section: Setting the Value Of Kmentioning

confidence: 77%

Self Organization and Self Maintenance of Mobile Ad Hoc Networks through Dynamic Topology Control

Blough

Resta

Santi

et al. 2010

Architecting Dependable Systems VII

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Abstract.One way in which wireless nodes can organize themselves into an ad hoc network is to execute a topology control protocol, which is designed to build a network satisfying specific properties. A number of basic topology control protocols exist and have been extensively analyzed. Unfortunately, most of these protocols are designed primarily for static networks and the protocol designers simply advise that the protocols should be repeated periodically to deal with failures, mobility, and other sources of dynamism. However, continuously maintaining a network topology with basic connectivity properties is a fundamental requirement for overall network dependability. Current approaches consider failures only as an afterthought or take a static fault tolerance approach, which results in extremely high energy usage and low throughput. In addition, most of the existing topology control protocols assume that transmission power is a continuous variable and, therefore, nodes can choose an arbitrary power value between some minimum and maximum powers. However, wireless network interfaces with dynamic transmission power control permit the power to be set to one of a discrete number of possible values. This simple restriction complicates the design of the topology control protocol substantially. In this paper, we present a set of topology control protocols, which work with discrete power levels and for which we specify a version that deals specifically with dynamic networks that experience failures, mobility, and other dynamic conditions. Our protocols are also novel in the sense that they are the first to consider explicit coordination between neighboring nodes, which results in more efficient power settings. In this chapter, we present the design of these topology control protocols, and we report on extensive simulations to evaluate them and compare their performance against existing protocols. The results demonstrate that our protocols produce very similar topologies as the best protocols that assume power is a continuous variable, while having very low communication cost and seamlessly handling failures and mobility.

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“…In this model, the radio signal strength (power) at a distance d from the transmitter is given by P/d α , where P is the transmission power and α > 2 is the path loss coefficient [16] (the actual value of the constant α depends on the environment -e.g., indoor or outdoor) 2 . Up to technical details, our results can be extended to more general radio propagation models that accounts for irregular radio coverage area, such as the cost-based model proposed in [19], which is shown to closely approximate log-normal shadowing propagation. In the following, we assume all nodes use the same transmit power, an arbitrary constant P .…”

Section: B Radio Signal Propagationmentioning

confidence: 89%

“…In [4], Brar et al present a localized, distributed implementation of the GreedyPhysical scheduling algorithm presented in [3], which thus achieves the same approximation bounds (under the approximate SINR interference model described above). In [19], Scheideler et al present a localized, distributed algorithm for building a dominating set under the exact SINR interference model. Both algorithms make extensive use of physical carrier sensing to achieve local computation at the nodes, while guaranteeing algorithm operations under the global SINR interference model.…”

Section: Related Workmentioning

confidence: 99%

Approximation Algorithms for Wireless Link Scheduling With SINR-Based Interference

Blough

Resta

Santi

2010

IEEE/ACM Trans. Networking

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Abstract-In this paper, we consider the classical problem of link scheduling in wireless networks under an accurate interference model, in which correct packet reception at a receiver node depends on the signal to interference plus noise ratio (SINR). While most previous work on wireless networks has addressed the scheduling problem using simplistic graph-based or distancebased interference models, a few recent papers have investigated scheduling with SINR-based interference models. However, these papers have either used approximations to the SINR model or have ignored important aspects of the problem. We study the problem of wireless link scheduling under the exact SINR model, and present the first known true approximation algorithms for transmission scheduling under the exact model. We also introduce an algorithm with a proven approximation bound with respect to the length of the optimal schedule under primary interference. As an aside, our study identifies a class of "difficult to schedule" links, which hinder the derivation of tighter approximation bounds. Furthermore, we characterize conditions under which scheduling under SINR-based interference is within a constant factor from optimal under primary interference, which implies that secondary interference only degrades performance by a constant factor in these situations.Index Terms-Wireless link scheduling, spatial-TDMA, SINRbased interference model, approximation algorithms.

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An O(log n) dominating set protocol for wireless ad-hoc networks under the physical interference model

Cited by 101 publications

References 31 publications

The abstract MAC layer

The abstract MAC layer

Self Organization and Self Maintenance of Mobile Ad Hoc Networks through Dynamic Topology Control

Approximation Algorithms for Wireless Link Scheduling With SINR-Based Interference

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