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Energy Efficient Sensor Activation for Water Distribution Networks Based on Compressive Sensing
KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.ORCID-id: 0000-0002-1934-9208
KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.
KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.ORCID-id: 0000-0001-9810-3478
KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.ORCID-id: 0000-0002-5407-0835
2015 (engelsk)Inngår i: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 33, nr 12, s. 2997-3010Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The recent development of low cost wireless sensors enables novel internet-of-things (IoT) applications, such as the monitoring of water distribution networks. In such scenarios, the lifetime of the wireless sensor network (WSN) is a major concern, given that sensor node replacement is generally inconvenient and costly. In this paper, a compressive sensing-based scheduling scheme is proposed that conserves energy by activating only a small subset of sensor nodes in each timeslot to sense and transmit. Compressive sensing introduces a cardinality constraint that makes the scheduling optimization problem particularly challenging. Taking advantage of the network topology imposed by the IoT water monitoring scenario, the scheduling problem is decomposed into simpler subproblems, and a dynamic-programming-based solution method is proposed. Based on the proposed method, a solution algorithm is derived, whose complexity and energy-wise performance are investigated. The complexity of the proposed algorithm is characterized and its performance is evaluated numerically via an IoT emulator of water distribution networks. The analytical and numerical results show that the proposed algorithm outperforms state-of-the-art approaches in terms of energy consumption, network lifetime, and robustness to sensor node failures. It is argued that the derived solution approach is general and it can be potentially applied to more IoT scenarios such as WSN scheduling in smart cities and intelligent transport systems.

sted, utgiver, år, opplag, sider
IEEE , 2015. Vol. 33, nr 12, s. 2997-3010
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-178154DOI: 10.1109/JSAC.2015.2481199ISI: 000365223600040Scopus ID: 2-s2.0-84960131576OAI: oai:DiVA.org:kth-178154DiVA, id: diva2:877656
Forskningsfinansiär
Wireless@kth
Merknad

QC 20151215

Tilgjengelig fra: 2015-12-07 Laget: 2015-12-07 Sist oppdatert: 2017-12-01bibliografisk kontrollert
Inngår i avhandling
1. Wireless Sensor Networks in Smart Cities: The Monitoring of Water Distribution Networks Case
Åpne denne publikasjonen i ny fane eller vindu >>Wireless Sensor Networks in Smart Cities: The Monitoring of Water Distribution Networks Case
2016 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
Abstract [en]

The development of wireless sensor networks (WSNs) is making it possible to monitor our cities. Due to the small size of the sensor nodes, and their capabilities of transmitting data remotely, they can be deployed at locations that are not easy or impossible to access, such as the pipelines of water distribution networks (WDNs), which plays an important role in protecting environment and securing public health.

  The design of WSNs for WDNs faces major challenges. Generally, WSNs are resource-limited because most of the sensor nodes are battery powered. Thus, their resource allocation has to be carefully controlled. The thesis considers two prominent problems that occur when designing WSNs for WDNs: scheduling the sensing of the nodes of static WSNs, and sensor placement for mobile WSNs. These studies are reported in the thesis from three published or submitted papers. In the first paper, the scheduling of sleep/sensing for each sensor node is considered to maximize the whole WSNs lifetime while guaranteeing a monitoring performance constraint. The problem is transformed into an energy balancing problem, and solved by a dynamic programming based algorithm. It is proved that this algorithm finds one of the optimal solutions for the energy balancing problem. In the second paper, the question of how the energy balancing problem approximates the original scheduling problem is addressed. It is shown that even though these two problems are not equivalent, the gap of them is small enough. Thus, the proposed algorithm for the energy balancing problem can find a good approximation solution for the original scheduling problem. The second part of the thesis considers the use of mobile sensor nodes. Here, the limited resource is the number of available such mobile nodes. To maximize the monitoring coverage in terms of population, an optimization problem for determining the releasing locations for the mobile sensor nodes is formulated. An approximate solution algorithm based on submodular maximization is proposed and its performance is investigated. Beside WDNs, WSN applications for smart cities share a common characteristic: the area to monitor usually has a network structure. Therefore, the studies of this thesis can be potentially generalized for several IoT scenarios.

sted, utgiver, år, opplag, sider
KTH Royal Institute of Technology, 2016. s. 21
Serie
TRITA-EE, ISSN 1653-5146 ; 2016:60
Emneord
Integer Programming, Nonconvex Optimization, Network Lifetime, Dynamic
HSV kategori
Forskningsprogram
Elektro- och systemteknik
Identifikatorer
urn:nbn:se:kth:diva-185453 (URN)978-91-7595-964-1 (ISBN)
Presentation
2016-05-10, Q2, OSQULDAS VÄG 10, Stockholm, 10:00 (engelsk)
Opponent
Veileder
Merknad

QC 20160419

Tilgjengelig fra: 2016-04-20 Laget: 2016-04-19 Sist oppdatert: 2020-01-07bibliografisk kontrollert

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