http://www.eecs.ucf.edu/~dcm/Teaching/COT4810-Spring2011/Literature/SensorNetworksSurvey.pdf

Wireless sensor networks: a survey

The advancement in wireless communications and electronics has enabled the development of low-cost sensor networks. The sensor networks can be used for various application areas (e.g., health, military, home). For different application areas, there are different technical issues that researchers are currently resolving. The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections. This article also points out the open research issues and intends to spark new interests and developments in this field.

/pdf/a-survey-on-sensor-networks-5beav0ez6k.pdf

A survey on sensor networks

Wireless Communications

This paper proposes S-MAC, a medium-access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect sensor networks to be deployed in an ad hoc fashion, with individual nodes remaining largely inactive for long periods of time, but then becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in almost every way: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important. S-MAC uses three novel techniques to reduce energy consumption and support self-configuration. To reduce energy consumption in listening to an idle channel, nodes periodically sleep. Neighboring nodes form virtual clusters to auto-synchronize on sleep schedules. Inspired by PAMAS, S-MAC also sets the radio to sleep during transmissions of other nodes. Unlike PAMAS, it only uses in-channel signaling. Finally, S-MAC applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data move through the network. We evaluate our implementation of S-MAC over a sample sensor node, the Mote, developed at University of California, Berkeley. The experiment results show that, on a source node, an 802.11-like MAC consumes 2–6 times more energy than S-MAC for traffic load with messages sent every 1–10s.

An Energy-Efficient MAC Protocol for Wireless Sensor Networks

This paper proposes S-MAC, a medium-access control (MAC) protocol designed for wireless sensor networks Wireless sensor networks use battery-operated computing and sensing devices A network of these devices will collaborate for a common application such as environmental monitoring We expect sensor networks to be deployed in an ad hoc fashion, with individual nodes remaining largely inactive for long periods of time, but then becoming suddenly active when something is detected These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 80211 in almost every way: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important S-MAC uses three novel techniques to reduce energy consumption and support self-configuration To reduce energy consumption in listening to an idle channel, nodes periodically sleep Neighboring nodes form virtual clusters to auto-synchronize on sleep schedules Inspired by PAMAS, S-MAC also sets the radio to sleep during transmissions of other nodes Unlike PAMAS, it only uses in-channel signaling Finally, S-MAC applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data move through the network We evaluate our implementation of S-MAC over a sample sensor node, the Mote, developed at University of California, Berkeley The experiment results show that, on a source node, an 80211-like MAC consumes 2-6 times more energy than S-MAC for traffic load with messages sent every 1-10 s

/pdf/an-energy-efficient-mac-protocol-for-wireless-sensor-jh99luvtj3.pdf

An energy-efficient MAC protocol for wireless sensor networks

Advances in processor, memory, and radio technology will enable small and cheap nodes capable of sensing, communication, and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed-diffusion paradigm for such coordination. Directed diffusion is data-centric in that all communication is for named data. All nodes in a directed-diffusion-based network are application aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network (e.g., data aggregation). We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network analytically and experimentally. Our evaluation indicates that directed diffusion can achieve significant energy savings and can outperform idealized traditional schemes (e.g., omniscient multicast) under the investigated scenarios.

/pdf/directed-diffusion-for-wireless-sensor-networking-57x2fro512.pdf

Directed diffusion for wireless sensor networking

In most distributed systems, naming of nodes for low-level communication leverages topological location (such as node addresses) and is independent of any application. In this paper, we investigate an emerging class of distributed systems where low-level communication does not rely on network topological location. Rather, low-level communication is based on attributes that are external to the network topology and relevant to the application. When combined with dense deployment of nodes, this kind of named data enables in-network processing for data aggregation, collaborative signal processing, and similar problems. These approaches are essential for emerging applications such as sensor networks where resources such as bandwidth and energy are limited. This paper is the first description of the software architecture that supports named data and in-network processing in an operational, multi-application sensor-network. We show that approaches such as in-network aggregation and nested queries can significantly affect network traffic. In one experiment aggregation reduces traffic by up to 42% and nested queries reduce loss rates by 30%. Although aggregation has been previously studied in simulation, this paper demonstrates nested queries as another form of in-network processing, and it presents the first evaluation of these approaches over an operational testbed.

/pdf/building-efficient-wireless-sensor-networks-with-low-level-34iaj4dgr4.pdf

Building efficient wireless sensor networks with low-level naming

Energy is a critical resource in sensor networks. MAC protocols such as S-MAC and T-MAC coordinate sleep schedules to reduce energy consumption. Recently, lowpower listening (LPL) approaches such as WiseMAC and B-MAC exploit very brief polling of channel activity combined with long preambles before each transmission, saving energy particularly during low network utilization. Synchronization cost, either explicitly in scheduling, or implicitly in long preambles, limits all these protocols to duty cycles of 1-2%. We demonstrate that ultra-low duty cycles of 0.1% and below are possible with a new MAC protocol called scheduled channel polling (SCP). This work prompts three new contributions: First, we establish optimal configurations for both LPL and SCP under fixed conditions, developing a lower bound of energy consumption. Under these conditions, SCP can extend lifetime of a network by a factor of 3-6 times over LPL. Second, SCP is designed to adapt well to variable traffic. LPL is optimized for known, periodic traffic, and long preambles become very costly when traffic varies. In one experiment, SCP reduces energy consumption by a factor of 10 under bursty traffic. We also show how SCP adapts to heavy traffic and streams data in multi-hop networks, reducing latency by 85% and energy by 95% at 9 hops. Finally, we show that SCP can operate effectively on recent hardware such as 802.15.4 radios. In fact, power consumption of SCP decreases with faster radios, but that of LPL increases.

/pdf/ultra-low-duty-cycle-mac-with-scheduled-channel-polling-1gvt0kj7h7.pdf

Ultra-low duty cycle MAC with scheduled channel polling

A distinguishing characteristic of wireless sensor networks is the opportunity to exploit characteristics of the application at lower layers. This approach is encouraged by device resource constraints, and acceptable because devices are inexpensive and numerous enough that they can be dedicated to specific applications. Many data dissemination protocols have been proposed for multi-hop communication in sensor networks, each evaluated in some scenario. The premise of this paper is that, if protocols are designed to exploit application requirements, then no one protocol can be optimized for all applications.Instead, a family of protocols are needed, with guidance to match protocol to application. We show through field experiments with two tracking applications that choice of diffusion algorithm can affect application performance by 40--60%. These applications motivate the design of two new diffusion algorithms: push and one-phase pull diffusion. We describe these algorithms in comparison to previous algorithms, then systematically explore their performance as the number of sinks and sources, the traffic rate and node placement varies, and with and without geographic proximity in node placement and with and without geographically scoped communication. We characterize algorithm performance and highlight the effect of the choice of algorithm parameters. The end result of this work are guidelines to help application developers to match dissemination algorithms to application performance requirements.

/pdf/matching-data-dissemination-algorithms-to-application-zhrpnbxwey.pdf

Fabio Silva

Papers

Directed diffusion for wireless sensor networking

Building efficient wireless sensor networks with low-level naming

Ultra-low duty cycle MAC with scheduled channel polling

Matching data dissemination algorithms to application requirements

Matching Data Dissemination Algorithms to Application Requirements