A Survey on Virtualization of Wireless Sensor Networks

Islam, Md. Motaharul; Hassan, Mohammad Mehedi; Lee, Ga‐Won; Huh, Eui‐Nam

doi:10.3390/s120202175

Cited by 89 publications

(61 citation statements)

References 41 publications

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“…Taking this to an extreme, one could consider a scenario whereby every node in the world is physically part of a single WSN, but which is virtually segregated into smaller sub-networks (the concept of a virtual sensor network, VSN [14]). However, we believe that the approach taken by OI-MAC is more achievable, as stakeholders can retain real ownership of their own network, and interconnection across a real boundary can be moderated by future higher-layer trading protocols.…”

Section: Enabling Direct Interconnectionmentioning

confidence: 99%

Opportunistic Direct Interconnection between Co-Located Wireless Sensor Networks

Jiang

Merrett

Harris

2013

2013 22nd International Conference on Computer Communication and Networks (ICCCN)

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Abstract-Wireless sensor networks are usually designed to avoid interaction with other networks. To share information, they are usually connected via a backbone network (e.g. the Internet) using gateways. The realization of visions for pervasive computing depends upon effective interconnection between individual networks. As the number of deployed sensor networks increases, the chance of any network having multiple neighbors also increases. In this paper, we argue that a paradigm shift towards 'opportunistic direct interconnection' is required. This enables one network to share information or resources with neighboring networks that it was unaware of at design-time. We present OI-MAC, which supports automatic neighbor discovery and cross-boundary data exchange without sacrificing the independence of each network. The effects of discovery and cross-boundary data injection are evaluated using both analytical models and network simulation. Initial results indicate that neighbor discovery has little effect on latency, while energy consumption increases insignificantly compared to ordinary operations of each node. If network traffic is doubled by packets 'injected' from a neighboring network, latency increases by around 7% while average power consumption increases by 20%.

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Section: Enabling Direct Interconnectionmentioning

confidence: 99%

Opportunistic Direct Interconnection between Co-Located Wireless Sensor Networks

Jiang

Merrett

Harris

2013

2013 22nd International Conference on Computer Communication and Networks (ICCCN)

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“…The emergence of shared sensor networks has stimulated research efforts in the field of novel programming abstractions at the node level and management framework at the network level to support multiple applications over a shared physical infrastructure [7], [8].…”

Section: Related Workmentioning

confidence: 99%

“…Constraint (8) imposes that all the generated data are delivered to the set of sinks. The last term of this expression allows the sinks to be running applications as well.…”

Section: System Model and Optimization Frameworkmentioning

confidence: 99%

An Optimization Framework for Resource Allocation in Virtual Sensor Networks

Delgado

Gállego

Canales

et al. 2015

2015 IEEE Global Communications Conference (GLOBECOM)

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Abstract-We propose an optimization framework to perform resource allocation in virtual sensor networks. Sensor network virtualization is a promising paradigm to improve flexibility of wireless sensor networks which allows to dynamically assign physical resources to multiple stakeholder applications. The proposed optimization framework aims at maximizing the total number of applications which can share a common physical network, while accounting for the distinguishing characteristics and limitations of the wireless sensor environment (limited storage, limited processing power, limited bandwidth, tight energy consumption requirements). The proposed framework is finally applied to realistic network topologies to assess the gain involved in letting multiple applications share a common physical network with respect to one-application, one-network vertical design approaches.

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“…In general, different types of WSN virtualization methods exist, node-based virtualization (NodBV), network-based virtualization (NetBV) [1][2][3]. But the methods are not suitable for IoT systems that meet the demands of a large number of clients.…”

Section: Introductionmentioning

confidence: 99%

“…Virtualization on cloud systems completely isolates the infrastructure from the clients. Thus, the clients are only interested in resource choice [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Alternative Resource Allocation Model for Dynamic Resource Sharing WSN Systems

Yıldırım¹,

Tatar²

2017

Fifth International Conference on Advances in Computing, Electronics and Communication - ACEC 2017

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Abstract-One of the major solutions to the interoperability problem of different wireless sensor networks (WSNs) which are in different locations is the use of WSN virtualization techniques. In these types of systems, there is generally a provider system to which the heterogeneous WSNs are registered. Through the provider system, clients can choose different resources existing in the different WSNs and establish their own virtual networks. In virtualization, the resource choice/allocation operation is one of the initial processes. This process is important to clients, the provider and efficient system maintenance. Current resource choice/allocation models used in IoT WSN providers generally take into account client parameters. However, other parameters are also available for optimum resource allocation, including available energy levels of the nodes in the sub-WSNs, data traffic in the sub-WSNs, processing rate of the physical nodes. In addition, the sub-WSNs registered to the provider can have different skills and features. The sub-WSN parameters must be taken into account in the process of the resource choice/allocation. In the paper, an alternative resource allocation model which considers these critical parameters is proposed. In the model, which is analytically explained, both client-side and provider-side parameters are considered. Thus, the systems in the sub WSNs can operate for a longer time and more economically

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A Survey on Virtualization of Wireless Sensor Networks

Cited by 89 publications

References 41 publications

Opportunistic Direct Interconnection between Co-Located Wireless Sensor Networks

Opportunistic Direct Interconnection between Co-Located Wireless Sensor Networks

An Optimization Framework for Resource Allocation in Virtual Sensor Networks

Alternative Resource Allocation Model for Dynamic Resource Sharing WSN Systems

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