Middleware for Wireless Sensor Networks: A Comparative Analysis

Masri, Wassim; Mammeri, Zoubir

doi:10.1109/icnpcw.2007.4351509

Cited by 7 publications

(10 citation statements)

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“…As we notice, flows transmitted from cluster C 4 1 to cluster C 4 8 are all sent on the first, second and third time slots of the superframe because no overhearing could occur between those clusters. Note that cluster C 4 6 was chosen to be represented in the superframe because it contains the maximum number of nodes (i.e. the maximum number of flows) among its peers.…”

Section: Superframe Length Computationmentioning

confidence: 99%

“…The total number of represented nodes in the superframe (leaf nodes + intermediate nodes) is computed using the function Ns(x) presented in the previous section. Formula (4) is simply obtained by substituting L(C h i ) by Ns(C h i ) in formula (7). This is depicted in Fig.…”

Section: Superframe Length Computationmentioning

confidence: 99%

“…Ch init (C 4 3 ) = 2 and MCh(C 4 3 ) = 6 (computed using formula (9)). In this simulation, we increase the number of child nodes in this cluster gradually until we reach MCh, (for Ch(C 4 3 ) = 3, 4, 5, 6, the superframe length is computed using the 2nd formula of rule (10)), then we exceed it (for Ch(C 4 3 ) = 7, 8, 9, 10, 11, the superframe length is computed using the 3rd formula of rule (10)). As we notice, bandwidth decreases gradually while adding nodes, then it starts decreasing faster when it exceeds MCh.…”

Section: Relationship Between Network Density and Bandwidthmentioning

confidence: 99%

“…protocols, energy consumption [3], and many other issues like time synchronization, geographical location and security, the QoS support remains one of the least explored areas in the WSN domain [4], since most of the research industry is following the actual trend in focusing on the energy consumption problem and the related issues.…”

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confidence: 99%

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Mapping density to bandwidth in tree-based wireless sensor networks

Masri

Mammeri

2009

Telecommun Syst

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Sensors in a wireless sensor network (WSN) are often resource constrained: they are limited in processing speed, storage capacity and energy. Therefore, most of the research projects in WSN domain are aiming at the energy issue, while leaving some equally crucial issues unexplored, like the QoS support. In this paper, we present QoS support in WSN while highlighting the QoS mapping issue, a complex process in which QoS parameters are translated from level to level and we present a case study of a TDMA treebased clustered WSN, where network density at the user level is mapped to bandwidth at the network level. We end our paper with simulations that prove our formulas and highlight the relationships between QoS parameters.

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Section: Superframe Length Computationmentioning

confidence: 99%

Section: Superframe Length Computationmentioning

confidence: 99%

Section: Relationship Between Network Density and Bandwidthmentioning

confidence: 99%

mentioning

confidence: 99%

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Mapping density to bandwidth in tree-based wireless sensor networks

Masri

Mammeri

2009

Telecommun Syst

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“…A proposed solution is the deployment of middleware that provides an intermediate software architecture and simplifies the access to different kinds of sensor technologies [7]. Other approaches consider enhancing this middleware with dynamic programmable features [8] and sensor clustering into virtual machines viewed as applications [9].…”

Section: Related Workmentioning

confidence: 99%

MINDiT: A framework for media independent access to things

Corujo¹,

Lebre²,

Gomes³

et al. 2012

Computer Communications

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a b s t r a c tDeploying smart environments often implies a plethora of co-existing devices and services, each with their own set of features, requirements and interfacing characteristics. These intricate scenarios are further exacerbated when such devices are coupled with networking capabilities, globalizing their interaction opportunities to create the so-called Internet of Things. In such interconnected heterogeneous environments, the joint operation of entities requires a flexible framework that enables and simplifies interfacing between elements. In this paper, we propose MINDiT, a framework that provides a common abstract interface towards the communication support with different entities. It incorporates cross-layer mechanisms inspired on the existing IEEE 802.21 technology, suitably modified to facilitate and optimize deployment in scenarios featuring both high-level, and low-powered network-restricted entities. MINDiT was validated through a prototype built over an open-source IEEE 802.21 implementation. We further compared its signaling impact against other solutions, and evaluated its performance over a smart environment featuring a multimedia scenario with multiple devices and services.

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Middleware for Wireless Sensor Networks: A Survey

Wang

Cao

et al. 2008

J. Comput. Sci. Technol.

177

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Wireless Sensor Networks (WSNs) have found more and more applications in a variety of pervasive computing environments. However, how to support the development, maintenance, deployment and execution of applications over WSNs remains to be a nontrivial and challenging task, mainly because of the gap between the high level requirements from pervasive computing applications and the underlying operation of WSNs. Middleware for WSN can help bridge the gap and remove impediments. In recent years, research has been carried out on WSN middleware from different aspects and for different purposes. In this paper, we provide a comprehensive review of the existing work on WSN middleware, seeking for a better understanding of the current issues and future directions in this field. We propose a reference framework to analyze the functionalities of WSN middleware in terms of the system abstractions and the services provided. We review the approaches and techniques for implementing the services. On the basis of the analysis and by using a feature tree, we provide taxonomy of the features of WSN middleware and their relationships, and use the taxonomy to classify and evaluate existing work. We also discuss open problems in this important area of research.ularity of WSN-based applications.WSN middleware helps the programmer develop applications in several ways. First, it provides appropriate system abstractions, so that the application programmer can focus on the application logic without caring too much about the lower level implementation details. Second, it provides reusable code services, such as code update, and data services, such as data filtering, so that the application programmer can deploy and execute the application without being troubled with complex and tedious functions. Third, it helps the programmer in network infrastructure management and adaptation by providing efficient resource services, e.g., power management. It also supports system integration, monitoring, as well as system security.

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Middleware for Wireless Sensor Networks: A Comparative Analysis

Cited by 7 publications

References 0 publications

Mapping density to bandwidth in tree-based wireless sensor networks

Mapping density to bandwidth in tree-based wireless sensor networks

MINDiT: A framework for media independent access to things

Middleware for Wireless Sensor Networks: A Survey

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