Scale-free, self-organizing very large sensor networks (original) (raw)

Self-organization of Very Large Sensor Networks Based on Small-worlds Principles

2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 2009

We study networks consisting of a very large number of tiny and inexpensive sensors and introduce SWAS (Small-Worlds of Anonymous Sensors), an algorithm combining self-organization based upon smallworlds principles and Medium Access Control based upon a stack protocol for VLSNs and we report on a preliminary study of the algorithm. The nodes of Very Large Sensor Networks (VLSN) have limited resources; to reduce the power consumption the processor is less powerful and the amount of storage available is smaller than those of traditional sensor networks. Moreover, the nodes are indistinguishable from one another; they do not have a physical address, as required by the traditional communication protocols. VLSNs mimic biological systems where individual cells of the same type are indistinguishable. Small-worlds networks [11] combine two desirable features of networks namely high clustering and small path length.

Self-organizing sensor networks

2008 3rd International Symposium on Wireless Pervasive Computing, 2008

In this paper we propose a scheme for selforganizing sensor networks; the scheme allows a sensor network to adapt to topological changes, include new batches of sensors, and disregard the sensors that have depleted their power reserves, or have been compromised. The algorithm for self-organization allows the sensor network to carry out its mission, has built-in provisions for information assurance, and extends its lifetime by reducing the power consumption; it minimizes the number of collisions experienced by a sensor when it transmits and maximizes the time a sensor is either idle or dedicated to monitoring and/or internal data processing.

Self-organization in sensor networks

Journal of Parallel and Distributed Computing, 2004

In an effort to better guide research into self-configuring wireless sensor networks, we discuss a technical definition of the term self-organization. We define a selforganizing system as one where a collection of units coordinate with each other to form a system that adapts to achieve a goal more efficiently. We then lay out some conditions that must hold for a system to meet this definition and discuss some examples of self-organizing systems. Finally, we explore some of the ways this definition applies to wireless sensor networks.

Self-Organizing Distributed Sensor Networks

2000

Advances in CMOS IC and micro electrical-mechanical systems (MEMS) technology are enabling construction of low-cost building blocks each of which incorporates sensing, signal processing, and wireless communications. Collections of these integrated microsensor nodes may be formed into sensor networks in a wide variety of ways, with characteristics that depend on the specific application - the total number of nodes, the

A Scalable, Self-organizing Communications System for very large Wireless Sensor Networks

2015

Wireless Sensor Networks (WSNs) are made of a large amount of small devices that are able to sense changes in the environment and communicate these changes throughout the network. An example of such network is a photo voltaic (PV) power plant, where there is a sensor connected to each solar panel. The task of each sensor is to sense the output of the panel which is then sent to a central node for processing. Even though low data rate is employed in WSNs, other challenging issues appear in the network. Challenges are mostly related to the reliability of the communication links and to the energy efficiency. Moreover, as the network grows, it becomes impractical and even impossible to configure all these nodes manually. The use of self-organization and autoconfiguration algorithms becomes essential in this context. Also, because of the “manyto-one” feature of the communication in WSNs, the wireless interferences and the collisions, the scheduling of data collection becomes a challengin...

A Cellular Self-Organization Architecture for Wireless Sensor Networks

Wireless sensor networks are composed of large number of sensor nodes, which are limited in resources i.e. memory, energy and computation power. Sensor network life time is directly related to nodes energy. Wireless sensor networks are expected to be capable of self-organization in an efficient, reliable and continues manner during the life time of the network. Self-organization of wireless sensor networks are usually involved in partitioning the network into connected groups or clusters and is challenging task because of limited bandwidth and energy resources available in these networks. In this paper we propose a new cellular self-organized architecture for wireless sensor networks that extends the network life by efficiently utilizing nodes energy and distribute management tasks to support the scalability of management system in a densely deployed sensor networks. In our solution the network is partitioned into a virtual grid of cells. A cell manager and a gateway node are chosen in each cell to perform management tasks. Cell manager and gateway nodes coordinate with each other to perform management with minimum energy consumption. We assume a homogenous network where all nodes are equal in resources.

Novel Architecture of Self-organized Mobile Wireless Sensor Networks

Journal of Computing Science and Engineering, 2015

Self-organization of distributed wireless sensor nodes is a critical issue in wireless sensor networks (WSNs), since each sensor node has limited energy, bandwidth, and scalability. These issues prevent sensor nodes from actively collaborating with the other types of sensor nodes deployed in a typical heterogeneous and somewhat hostile environment. The automated self-organization of a WSN becomes more challenging as the number of sensor nodes increases in the network. In this paper, we propose a dynamic self-organized architecture that combines tree topology with a drawn-grid algorithm to automate the self-organization process for WSNs. In order to make our proposed architecture scalable, we assume that all participating active sensor nodes are unaware of their primary locations. In particular, this paper presents two algorithms called active-tree and drawn-grid. The proposed active-tree algorithm uses a tree topology to assign node IDs and define different roles to each participating sensor node. On the other hand, the drawn-grid algorithm divides the sensor nodes into cells with respect to the radio coverage area and the specific roles assigned by the active-tree algorithm. Thus, both proposed algorithms collaborate with each other to automate the self-organizing process for WSNs. The numerical and simulation results demonstrate that the proposed dynamic architecture performs much better than a static architecture in terms of the self-organization of wireless sensor nodes and energy consumption.

Cellular self-organization architecture for wireless sensor networks

2008

Wireless sensor networks are composed of large number of sensor nodes, which are limited in resources i.e. memory, energy and computation power. Sensor network life time is directly related to nodes energy. Wireless sensor networks are expected to be capable of self-organization in an efficient, reliable and continues manner during the life time of the network. Self-organization of wireless sensor networks are usually involved in partitioning the network into connected groups or clusters and is challenging task because of limited bandwidth and energy resources available in these networks. In this paper we propose a new cellular self-organized architecture for wireless sensor networks that extends the network life by efficiently utilizing nodes energy and distribute management tasks to support the scalability of management system in a densely deployed sensor networks. In our solution the network is partitioned into a virtual grid of cells. A cell manager and a gateway node are chosen in each cell to perform management tasks. Cell manager and gateway nodes coordinate with each other to perform management with minimum energy consumption. We assume a homogenous network where all nodes are equal in resources.

A brief survey of self-organization in wireless sensor networks

Wireless Communications and Mobile Computing, 2007

Many natural and man-made systems exhibit self-organization, where interactions among components lead to system-wide patterns of behavior. This paper first introduces current, scientific understanding of self-organizing systems and then identifies the main models investigated by computer scientists seeking to apply self-organization to design large, distributed systems. Subsequently, the paper surveys research that uses models of self-organization in wireless sensor networks to provide a variety of functions: sharing processing and communication capacity; forming and maintaining structures; conserving power; synchronizing time; configuring software components; adapting behavior associated with routing, with disseminating and querying for information, and with allocating tasks; and providing resilience by repairing faults and resisting attacks. The paper closes with a summary of open issues that must be addressed before self-organization can be applied routinely during design and deployment of senor networks and other distributed, computer systems.