This paper presents a survey of state-of-the-art routing techniques in Wireless Sensor Networks (WSNs). Compared with traditional wireless networks, WSNs are characterized with denser levels of node deployment, higher unreliability of sensor nodes and severe power, computation and memory constraints. Various design challenges such as energy efficiency, data delivery models, quality of service, overheads etc., for routing protocols in WSNs are highlighted. We addressed most of the proposed routing methods along with scheme designs, benefits and result analysis wherever possible. The routing protocols discussed are classified into seven categories such as Data centric routing, Hierarchical routing, Location based routing, Negotiation based routing, Multipath based routing, Quality of Service (QoS) routing and Mobility based routing. This paper also compares the routing protocols against parameters such as power consumption, scalability, mobility, optimal routing and data aggregation. The paper concludes with possible open research issues in WSNs.

A survey on routing protocols in Wireless Sensor Networks

A wireless sensor network (WSN) consisting of a large number of tiny sensors can be an effective tool for gathering data in diverse kinds of environments. The data collected by each sensor is communicated to the base station, which forwards the data to the end user. Clustering is introduced to WSNs because it has proven to be an effective approach to provide better data aggregation and scalability for large WSNs. Clustering also conserves the limited energy resources of the sensors. This paper synthesises existing clustering algorithms in WSNs and highlights the challenges in clustering.

A survey on clustering algorithms for wireless sensor networks

The distributed nature and dynamic topology of Wireless Sensor Networks (WSNs) introduces very special requirements in routing protocols that should be met. The most important feature of a routing protocol, in order to be efficient for WSNs, is the energy consumption and the extension of the network's lifetime. During the recent years, many energy efficient routing protocols have been proposed for WSNs. In this paper, energy efficient routing protocols are classified into four main schemes: Network Structure, Communication Model, Topology Based and Reliable Routing. The routing protocols belonging to the first category can be further classified as flat or hierarchical. The routing protocols belonging to the second category can be further classified as Query-based or Coherent and non-coherent-based or Negotiation-based. The routing protocols belonging to the third category can be further classified as Location-based or Mobile Agent-based. The routing protocols belonging to the fourth category can be further classified as QoS-based or Multipath-based. Then, an analytical survey on energy efficient routing protocols for WSNs is provided. In this paper, the classification initially proposed by Al-Karaki, is expanded, in order to enhance all the proposed papers since 2004 and to better describe which issues/operations in each protocol illustrate/enhance the energy-efficiency issues.

Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey

A super-peer is a node in a peer-to-peer network that operates both as a server to a set of clients, and as an equal in a network of super-peers. Super-peer networks strike a balance between the efficiency of centralized search, and the autonomy, load balancing and robustness to attacks provided by distributed search. Furthermore, they take advantage of the heterogeneity of capabilities (e.g., bandwidth, processing power) across peers, which recent studies have shown to be enormous. Hence, new and old P2P systems like KaZaA and Gnutella are adopting super-peers in their design. Despite their growing popularity, the behavior of super-peer networks is not well understood. For example, what are the potential drawbacks of super-peer networks? How can super-peers be made more reliable? How many clients should a super-peer take on to maximize efficiency? we examine super-peer networks in detail, gaming an understanding of their fundamental characteristics and performance tradeoffs. We also present practical guidelines and a general procedure for the design of an efficient super-peer network.

Designing an Super-Peer Network

Clustering algorithms have emerged as an alternative powerful meta-learning tool to accurately analyze the massive volume of data generated by modern applications. In particular, their main goal is to categorize data into clusters such that objects are grouped in the same cluster when they are similar according to specific metrics. There is a vast body of knowledge in the area of clustering and there has been attempts to analyze and categorize them for a larger number of applications. However, one of the major issues in using clustering algorithms for big data that causes confusion amongst practitioners is the lack of consensus in the definition of their properties as well as a lack of formal categorization. With the intention of alleviating these problems, this paper introduces concepts and algorithms related to clustering, a concise survey of existing (clustering) algorithms as well as providing a comparison, both from a theoretical and an empirical perspective. From a theoretical perspective, we developed a categorizing framework based on the main properties pointed out in previous studies. Empirically, we conducted extensive experiments where we compared the most representative algorithm from each of the categories using a large number of real (big) data sets. The effectiveness of the candidate clustering algorithms is measured through a number of internal and external validity metrics, stability, runtime, and scalability tests. In addition, we highlighted the set of clustering algorithms that are the best performing for big data.

A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis

A wireless sensor network (WSN)consisting of a large number of tiny sensors can be an effective tool for gathering data in diverse kinds of environments. The data collected by each sensor is communicated to the base station, which forwards the data to the end user. Clustering is introduced to WSNs because it has proven to be an effective approach to provide better data aggregation and scalability for large WSNs. Clustering also conserves the limited energy resources of the sensors. This paper synthesises existing clustering algorithms news's and highlights the challenges in clustering.

A Survey on Clustering Algorithms for Wireless Sensor Networks

One of the major weaknesses of existing centralized algorithms in Wireless Sensor Network (WSN) routing is that sensor nodes are required to report their status (e.g. remaining energy level) to the central node (i.e. the Base Station ---BS) and receive configuration information from the BS (e.g. next hop routing). As a result, the WSNs suffer from high communication and/or computation overheads at sensor nodes to accommodate topology changes in the WSN. This paper proposes a novel scheme, called a Sensor Web (or S-Web), that organizes sensors into clusters based on their geographical location without requiring the sensors to have a Global Positioning System or actively locate themselves. The S-Web enables nodes to route data packets while consuming low energy in a decentralized manner. The model is self-organizing and distributed without the need of global network knowledge.

S-Web: An Efficient and Self-organizing Wireless Sensor Network Model

In this paper, we describe the performance of the B.A.T.M.A.N advanced (Batman-adv) protocol on an indoor Mesh Potato (MP) test bed. The MPs are small devices used for voice communications over the wireless medium but also supports data. The Batman-adv protocol is designed for ad hocwireless networks. We measure delay, packet loss in order to understand the MPs network performance. The experiments used packets of varying sizes over multiple hops. We analyze the data to see if the network latency for up to four hops is within the recommended boundaries set by ITU Recommendation G. 114. We also observe the how thenetwork's performance is affected by the varying packet sizes. Finally the experiments also reveal the common issues found on the wireless medium and also indoor testbeds.

Investigation into Batman-adv Protocol Performance in an Indoor Mesh Potato Testbed

A schedule-based approach, such as time division multiple access, is more efficient than a contention-based approach in terms of energy saving by switching sensors into sleeping mode. However, it does not use the transmission media effectively as each time slot is dedicated to a sensor and therefore cannot be used by others should it be idle. Moreover, a schedule-based approach requires a central node to manage and broadcast the schedule to other members, causing high delay and unscalability. On the other hand, contention-based protocols can be used in a distributed fashion. However, contention-based protocols such as IEEE 802.11 waste a lot of energy in idle listening. In this paper, we propose a hybrid approach between contention- and schedule-based protocols. The preliminary results using simulation and a test bed show that our proposed approach uses transmission media more efficiently, leading to lower delay while preserving energy for wireless sensor networks.

Hanh Le

Papers

A survey on clustering algorithms for wireless sensor networks

A Survey on Clustering Algorithms for Wireless Sensor Networks

S-Web: An Efficient and Self-organizing Wireless Sensor Network Model

Investigation into Batman-adv Protocol Performance in an Indoor Mesh Potato Testbed

An Efficient Hybrid Medium Access Control Technique for Digital Ecosystems