Near-Optimal Radio Use for Wireless Network Synchronization

Bradonjic, Milan; Kohler, Eddie; Ostrovsky, Rafail

doi:10.1007/978-3-642-05434-1_4

Cited by 9 publications

(20 citation statements)

References 44 publications

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“…1, for 𝑑 = 36 and two right shifts of length 0 and 10, respectively. We remark that the bound proved in this section is in fact more general than the subsequent independent work of [14], which appeared after our report [10]. Note that our bound holds for all values of 𝑑 and the two strings could be made identical by doubling the cost.…”

Section: Matching Upper Bound For Two Processorssupporting

confidence: 55%

Near-optimal radio use for wireless network synchronization

Bradonji

Kohler

Ostrovsky

2012

Theoretical Computer Science

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In this paper, we consider the model of communication where wireless devices can either switch their radios off to save energy (and hence, can neither send nor receive messages), or switch their radios on and engage in communication. The problem has been extensively studied in practice, in the setting such as deployment and clock synchronization of wireless sensor networks.We distill a clean theoretical formulation of minimizing radio use and present near-optimal solutions. Our base model ignores issues of communication interference, although we also extend the model to handle this requirement. We assume that nodes intend to communicate periodically, or according to some time-based schedule. Clearly, perfectly synchronized devices could switch their radios on for exactly the minimum periods required by their joint schedules. The main challenge in the deployment of wireless networks is to synchronize the devices' schedules, given that their initial schedules may be offset relative to one another (even if their clocks run at the same speed). In this paper we study how frequently the devices must switch on their radios in order to both synchronize their clocks and communicate. In this setting, we significantly improve previous results, and show optimal use of the radio for two processors and near-optimal use of the radio for synchronization of an arbitrary number of processors. In particular, for two processors we prove deterministic matching Θ( √ ) upper and lower bounds on the number of times the radio has to be on, where is the discretized uncertainty period of the clock shift between the two processors. (In contrast, all previous results for two processors are randomized). For = processors (for any positive < 1) we prove Ω( (1− )/2 ) is the lower bound on the number of times the radio has to be switched on (per processor), and show a nearly matching (in terms of the radio use)Õ( (1− )/2 ) randomized upper bound per processor. For ≥ 1 our algorithm runs with at most poly-log( ) radio invocations per processor. Our bounds also hold in a radio-broadcast model where interference must be taken into account.

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Section: Matching Upper Bound For Two Processorssupporting

confidence: 55%

Near-optimal radio use for wireless network synchronization

Bradonji

Kohler

Ostrovsky

2012

Theoretical Computer Science

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“…Second, this community has also focused on bounds that depend on duty-cycle and hence energy budget, which are of direct practical relevance. For these reasons, the bounds from [3,5] are not comparable to those that have been more commonly pursued, and also to those presented in this paper.…”

Section: Related Workcontrasting

confidence: 61%

“…Generic Approaches: Unlike the work described above that was specific to slotted or PI-based protocols, protocol-agnostic bounds were presented in [3,5]. In particular, they give an asymptotic latency bound in the form of Θ𝑑, where 𝑑 is "the discretized uncertainty period of the clock shift between the two processors" [5]. Hence, this bound depends on the degree of asynchrony between the clocks of a sender and a receiver.…”

Section: Related Workmentioning

confidence: 99%

Performance Limits of Neighbor Discovery in Wireless Networks

Kindt¹,

Chakraborty²

2021

Preprint

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Neighbor Discovery (ND) is the process employed by two wireless devices to discover each other. It is routinely used in a variety of devices ranging from small sensor nodes to smartphones, wireless keyboards and speakers. There are many different ND protocols, both in the scientific literature and also those employed in practice. All ND protocols involve devices sending beacons, and also listening for them. Protocols differ in terms of how the beacon transmissions and reception windows are scheduled, and the device sleeps in between consecutive transmissions and reception windows in order to save energy. A successful discovery constitutes a sending device's beacon overlapping with a receiving device's reception window. The goal of all ND protocols is to minimize the discovery latency. In spite of the ubiquity of ND protocols and active research on this topic for over two decades, the basic question "Given an energy budget, what is the minimum guaranteed ND latency?", however, still remains unanswered. Consequently, for many protocols, it is also not clear how to optimally parametrize them. Given the different kinds of protocols that exist, there has also been no standard way of comparing them and their performance. This paper, for the first time, answers the question on the best-achievable ND latency for a given energy budget. In order to compute this lower bound, we introduce a new concept called coverage maps, that allows us to analyze the ND procedure in a protocol-independent manner. Using it, we derive discovery latencies for different scenarios, e.g., when both devices have the same energy budgets, and both devices have different energy budgets. We also show that some existing protocols can be parametrized such that they perform optimally. The fact that the parametrizations of some other protocols were optimal was not known before, and can now be established using our technique. Our results are restricted to the case when a few devices discover each other at a time, as is the case in most real-life scenarios. When many devices need to discover each other simultaneously, packet collisions play a dominant role in the discovery latency and how to analyze such scenarios need further study.

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“…In Distributed Computing the problem of broadcast in sleeping radio networks was studied by King, Phillips, Saya and Young [22]. The problem of clock synchronization in networks with sleeping processors and variable initial wake-up times was studied by Bradonjic, Kohler and Ostrovsky [6], and by Barenboim, Dolev and Ostrovsky [2]. A special type of the sleeping model, in which processors are initially awake, and eventually enter a permanent sleeping state, was formalized by Feuilloley [12,13].…”

Section: Related Workmentioning

confidence: 99%

Deterministic Logarithmic Completeness in the Distributed Sleeping Model

Barenboim,

Maimon

2021

Preprint

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In this paper we provide a deterministic scheme for solving any decidable problem in the distributed sleeping model. The sleeping model [8,22] is a generalization of the standard message-passing model, with an additional capability of network nodes to enter a sleeping state occasionally. As long as a vertex is in the awake state, it is similar to the standard message-passing setting. However, when a vertex is asleep it cannot receive or send messages in the network nor can it perform internal computations. On the other hand, sleeping rounds do not count towards awake complexity. Awake complexity is the main complexity measurement in this setting, which is the number of awake rounds a vertex spends during an execution. In this paper we devise algorithms with worst-case guarantees on the awake complexity.We devise a deterministic scheme with awake complexity of O(log n) for solving any decidable problem in this model by constructing a structure we call Distributed Layered Tree. This structure turns out to be very powerful in the sleeping model, since it allows one to collect the entire graph information within a constant number of awake rounds. Moreover, we prove that our general technique cannot be improved in this model, by showing that the construction of distributed layered trees itself requires Ω(log n) awake rounds. This is obtained by a reduction from message-complexity lower bounds, which is of independent interest. Furthermore, our scheme also works in the CON GEST setting where we are limited to messages of size at most O(log n) bits. This result is shown for a certain class of problems, which contains problems of great interest in the research of the distributed setting. Examples for problems we can solve under this limitation are leader election, computing exact number of edges and average degree.Another result we obtain in this work is a deterministic scheme for solving any problem from a class of problems, denoted O-LOCAL, in O(log ∆ + log * n) awake rounds. This class contains various well-studied problems, such as MIS and (∆ + 1)-vertex-coloring. Our main structure in this case is a tree as well, but is sharply different from a distributed layered tree. In particular, it is constructed in the local memory of each processor, rather than distributively. Nevertheless, it provides an efficient synchronization scheme for problems of the O-LOCAL class.

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Near-Optimal Radio Use for Wireless Network Synchronization

Cited by 9 publications

References 44 publications

Near-optimal radio use for wireless network synchronization

Near-optimal radio use for wireless network synchronization

Performance Limits of Neighbor Discovery in Wireless Networks

Deterministic Logarithmic Completeness in the Distributed Sleeping Model

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