A case for centrally controlled wireless sensor networks

Hunkeler, Urs; Lombriser, Clemens; Truong, Hong Linh; Weiss, Beat

doi:10.1016/j.comnet.2012.12.019

Cited by 13 publications

(7 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mahmud and Rahmani discuss the feasibility of applying OpenFlow in WSN, and Luo et al further summarize the opportunities and challenges of integrating SDN and WSN. To accelerate the development of SDWSN, Hunkeler et al provide an in‐depth analysis of the advantages of central management over distributed management.…”

Section: Related Workmentioning

confidence: 99%

LCD: Light‐weight control model for data plane in software‐defined wireless sensor networks

Huang

2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

With the introduction of software‐defined networking (SDN) into wireless sensor networks (WSNs) to simplify network management and increase agility, software‐defined WSNs (SDWSNs) came into being. Since SDN adopts an idea of centralized control, reliable control is a necessary guarantee of its performance. However, in SDWSN, the unreliable wireless links pose a significant challenge to the reliable control of data plane. In view of this, this paper adopts the idea of separating the forwarding process of control flow and data flow and presents a light‐weight control model for data plane in SDWSN. Based on the network global view, the model constructs an independent control forwarding layer to route control flow. The light‐weight feature of this model lies in that there is no need to deploy additional control networks. Finally, we design a fast update algorithm for the control failure that may occur by searching for the replacement of neighboring control nodes and achieve efficient maintenance of the control forwarding layer. The simulation results show that the proposed model has shorter request‐response time than the original SDN‐WISE, and the impact on data plane forwarding performance is also within the acceptable range.

show abstract

Section: Related Workmentioning

confidence: 99%

LCD: Light‐weight control model for data plane in software‐defined wireless sensor networks

Huang

2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…The cornerstone of this algorithm is the concept of pairwise link conflict graph (PLCG). Let V D f.`i, ij /j`i 2 E, ij 2 fÂ 1 , Â 2 , : : : , Â R gg be a set where each link in E is replicated to form a pair with each data rate satisfying condition (1). We define a PLCG as an undirected graph G D .V, E/ where there exists an edge between two vertices v D .`, / and v0 D .`0, 0/ if one of the following conditions holds:…”

Section: Valid Matching Generation Algorithmmentioning

confidence: 99%

“…Although most of the state-of-the-art wireless sensor networks (WSNs) are formed by nodes that are designed to operate in an autonomous and distributed fashion, some recent works in the literature such as [1] or [2] indicate that centrally coordinated protocols at the network and the medium access control (MAC) layers are at least as efficient as distributed protocols in numerous settings while bringing other advantages such as code simplicity, ease of management, and observability. In particular, many WSN applications exhibit a regular traffic pattern by periodically collecting sensor measurements at a centralized entity known as the sink.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the throughput‐lifetime tradeoff in wireless sensor networks with link scheduling, rate adaptation, and power control

Kaddour¹

2015

Wireless Communications

View full text Add to dashboard Cite

Throughput and lifetime are usually conflicting objectives in designing wireless sensor networks; hence, the right balance needs to be found. With this aim in view, we address in this paper the problem of minimizing the frame length defined within a time division multiple access scheme and the problem of maximizing network lifetime subject to a maximum frame length. The pursued solution in either case leverages a wide range of parameters related to coverage, routing, transmission power, and data rate. Furthermore, it is consistent with the physical interference model. To this end, we rely on column generation technique to derive near-optimal solutions even when the integrality constraints on coverage and flow variables are enforced. Moreover, we propose a polynomial-time heuristic algorithm to solve efficiently the underlying NP-hard problem of concurrent link selection with discrete power control and rate adaptation. Simulation results show that our heuristic algorithm leads to solutions within 3% of optimality while saving around 99% of computation time. Besides, the results illustrate the significant impact of power control and rate adaptation on throughput and lifetime improvement. Interestingly, we found that network lifetime can be significantly prolonged when traffic demands are sufficiently low at the affordable cost of small decrease in throughput.

show abstract

“…Although most of the state-of-the-art wireless sensor networks (WSNs) are formed by nodes that are designed to operate in an autonomous and distributed fashion, some recent work in the literature such as [1] indicates that centrallycoordinated network and MAC layer protocols are at least as efficient as distributed protocols in numerous settings, while bringing several advantages such as code simplicity, ease of management or observability. In particular, many WSN applications exhibit a regular traffic pattern by periodically collecting sensor measurements at a centralized entity known as the sink.…”

Section: Introductionmentioning

confidence: 99%

An efficient method to minimize TDMA frame length in wireless sensor networks

Bakshi

Kaddour

Jaumard

et al. 2015

2015 IEEE Wireless Communications and Networking Conference (WCNC)

View full text Add to dashboard Cite

We address the problem of minimizing TDMA frame length in a wireless sensor network charged with monitoring a given set of targets. The problem reduces to finding a minimal set of so-called configurations that delivers data from the targets to a specially designated sink node, where each configuration is a set of links that can transmit concurrently without significant interference. We assume a SINR-based interference model. We use a column generation technique to derive nearoptimal solutions even when integrality constraints are enforced on coverage and flow variables. We also introduce a heuristic and a hybrid algorithm to efficiently solve the problem by leveraging a wide range of network parameters related to transmission power control, data rates, and routing. Our results show that significant gains in scalability can be obtained by using our methods.

show abstract

A case for centrally controlled wireless sensor networks

Cited by 13 publications

References 33 publications

LCD: Light‐weight control model for data plane in software‐defined wireless sensor networks

LCD: Light‐weight control model for data plane in software‐defined wireless sensor networks

Optimizing the throughput‐lifetime tradeoff in wireless sensor networks with link scheduling, rate adaptation, and power control

An efficient method to minimize TDMA frame length in wireless sensor networks

Contact Info

Product

Resources

About