In this paper, we propose an energy efficient MAC protocol for wireless sensor networks. In sensor networks, reducing energy consumption is one of the critical issues for extending network lifetime. One good solution to resolve this issue is introducing listen-sleep cycles, allowing sensor nodes to turn their transceiver off during sleep periods, which was adopted by S-MAC [1]. However, in S-MAC, due to the synchronized scheduling, transmission collisions will increase in heavy traffic situations, resulting in energy waste and low throughput. Hence, in this paper, we propose probabilistic scheduled MAC (PS-MAC), in which each node determines ‘listen’ or ‘sleep’ pseudo-randomly based on its own pre-wakeup probability and pre-wakeup probabilities of its neighbor nodes in each time slot. This allows the listen-sleep schedule of nodes in each transmitter and receiver pair to be synchronized, while maintaining those of the rest of nodes to be asynchronous. Therefore, collisions can be reduced even under heavy traffic conditions, resulting in reduced energy waste and high throughput. In addition, by dynamically adjusting the pre-wakeup probabilities of sensor nodes based on the change of the network environment, system throughput and latency can be further improved. Simulation results show that PS-MAC provides significant energy savings, low delay, and high network throughput.

The many-to-one communication nature of wireless sensor networks (WSNs) leads to an unbalanced traffic distribution, and, accordingly, sensor nodes closer to the base station have to transmit more packets than those at the periphery of the network. This problem causes the nodes closer to the base station to deplete their energy prematurely, forming a hole surrounding the base station. This phenomenon is called the energy hole problem, and it severely reduces the network lifetime. In this paper, we present a cooperative power-aware routing algorithm for uniformly deployed WSNs. The proposed algorithm is based on the idea of replacing the constant transmission range of relaying sensor nodes with an adjusted transmission range, in such a way that each individual node consumes its energy smoothly. We formulate the dynamic transmission range adjustment optimization (DTA) problem as a 0-1 Multiple Choice Knapsack Problem (0-1 MCKP) and present a dynamic programming method to solve the optimization problem. Simulations confirm that the proposed method helps to balance the energy consumption of sensor nodes, avoiding the energy hole problem and extending the network lifetime.

With Wireless Sensor Networks (WSNs) involving in diverse applications, the realistic analysis of energy consumption of a sensor node in an error-prone network environment is emerging as an elementary research issue. In this paper, we introduce a Distributed Communication Model (DCM) that can accurately determine the energy consumption through data communication from source to destination in error-prone network environments. The energy consumption is affected with the quality of link, which is characterized by symmetry, directivity, instability, and irregularity of the communication range of a sensor node. Due to weak communication links, significant packet loss occurs that affects the overall energy consumption. While other models unable to determine energy consumption due to lossy links in error-prone and unstable network environments, DCM can accurately estimate the energy consumption in such situations. We also perform comprehensive analysis of overheads caused by data propagation through multi-hop distributed networks. We validate DCM through both simulations and experiments using MICAz motes. Similarity of the results from energy consumption analysis with both simulations and experimentations shows that DCM is realistic, compared to other models in terms of accuracy and diversity of the environments.

This paper presents the design and performance evaluation of a power-controlled topology optimization and channel assignment scheme for Hybrid MAC (abbreviated PTOCA) in wireless sensor networks that require comparatively high data rate communications. In order to maximize the network performance, PTOCA is designed with a cross-layer concept of MAC and network layers, which provides multi-channel TDMA scheduling based on the information of the network topology optimized by transmission power control. The simulation results show that by using the proposed scheme, the network throughput and energy efficiency can be significantly improved. PTOCA is also more effective in improving the network performance when the nodes are uniformly deployed on the sensor field rather than when they are randomly distributed.

Temporal and spatial (geographical) fluctuations, which are present in the traffic of wireless sensor networks (WSNs), have a significant affect on the transmission performance and power consumption of WSNs. Several medium access control (MAC) mechanisms have been proposed for IEEE802.15.4 cluster-based WSNs to counter the temporal and spatial traffic fluctuations. However, these mechanisms cannot always achieve simultaneous improvement in both transmission performance and power consumption. In this paper, we propose two enhanced 2-level active period control mechanisms, BI&CAP control and BI&SD&CAP control, to achieve higher system performance than conventional control mechanisms. Various computer simulation results demonstrate the effectiveness of the proposed mechanisms for WSNs with various traffic fluctuations.

Traffic adaptive 2-level active period control has been proposed to enhance system performance in cluster-based wireless sensor networks (WSNs) employing IEEE 802.15.4 medium access control (MAC) under temporal and spatial (geographical) non-uniform traffic environments. This paper proposes an adaptive method of controlling the backoff window for traffic adaptive 2-level active period control. The proposed method adjusts the size of the backoff window according to the length of the current active period, which is determined by 2-level active period control, and the time position for channel access in the active period. The results evaluated through computer simulations reveal that the proposed method can improve throughput as well as achieve high energy efficiency in cluster-based WSNs with non-uniform traffic distributions.

This paper addresses the problem of sensor selection in wireless sensor networks (WSN) subject to a distortion constraint. To do so, first, a cost function is derived based on the spatial correlation obtained using the best estimation of the event source. Then, a new adaptive algorithm is proposed in which the number of active sensors is adaptively determined and the best topology of the active set is selected based on the add-one-sensor-node-at-a-time method. Simulations results show that the active sensors selected using the proposed cost function have less event distortion. Also, it is shown that the proposed sensor selection algorithm is near optimum and it has better performance than other algorithms with regard to the computational burden and distortion.

Wireless sensor networks (WSN) is composed of so many small sensor nodes which have limited resources. So the technique that raises energy efficiency is the key to prolong the network life time. In the paper, we propose an agent based framework which takes the biological characteristics of gene. The gene represents an operation policy to control agent behavior. Agents are aggregated to reduce duplicate transmissions in active period. And it selects next hop based on the information of neighbor agents. Among neighbors, the node which has enough energy is given higher priority. The base station processes genetic evolution to refine the behavior policy of agent. Each agent is taken latest gene and spread recursively to find the optimal gene. Our proposed framework yields sensor nodes that have the properties of self-healing, self-configuration, and self-optimization. Simulation results show that our proposed framework increases the lifetime of each node.

Secure access is one of the key concerns of wireless sensor networks (WSNs). In WSNs, because there are many dynamically mutable attributes, continuous access decisions and dynamic attribute updates should be important properties of access control. In addition, WSNs need low-complexity authentication protocols because of the constrained resources. However, the authentication protocols of most current security access schemes have relatively high complexity. More importantly, the access control models of existing schemes cannot provide attribute mutability and continuous decisions dynamically. To address above issues, we propose a dynamic secure access mechanism for WSNs. Firstly, we design a lightweight secure authentication protocol and dynamic access control based on security token and usage control (UCON), respectively. Then, the agent technology is adopted to implement the proposed secure access scheme. Secondly, we analyze the probability of the dynamic attribute update and decisions. Thirdly, we implement an instance of UCON. The implementation results indicate the feasibility of using UCON in WSNs. Finally, by evaluating and comparing with current schemes, the authentication protocol in our scheme presents several advantages including the low expenses in calculation, storage and communication. To our best knowledge, this paper is the first to realize next generation dynamic access control with attribute mutability and continuous decisions in WSNs.

A micro-power active-RFID LSI with an all-digital RF-transmitting scheme achieves experimental 10-m-distance communication with a 1-Mbps data rate in the 300-MHz frequency band. The IC consists of an RF transmitter and a power supply circuit. The RF transmitter generates wireless signals without a crystal. The power supply circuit controls the energy flow from the battery to the IC and offers intermittent operation of the RF transmitter. The IC draws 1.6 µA from a 3.4-V supply and is implemented in a 0.2-µm CMOS process in an area of 1 mm2. The estimated lifetime of the IC is over ten years with a coin-size battery.

We propose a geographic forwarding protocol for wireless sensor networks (WSNs). Our proposed protocol, named Landmark-based Location-Aware Routing (LLAR), intelligently combines greedy forwarding and a hole detouring technique utilizing landmark information. Compared to existing approaches, our proposal utilizes the feedback message from the sink node for discovery of the optimal path. Simulations show that our proposed scheme can eliminate a significant number of overhead messages compared to its counterparts, thereby further achieving higher energy efficiency.

A Wireless Sensor Network has sensor nodes which have limited computational power and memory size. Due to the nature of the network, the data is vulnerable to attacks. Thus, maintaining confidentiality is an important issue. To compensate for this problem, there are many countermeasures which utilize common or public key cryptosystems that have been proposed. However, these methods have problems with establishing keys between the source and the destination nodes. When these two nodes try to establish new keys, they must exchange information several times. Also, the routes of the Wireless Sensor Networks can change frequently due to an unstable wireless connection and batteries running out on sensor nodes. These problems of security and failure become more serious as the number of nodes in the network increases. In this paper, we propose a new data distribution method to compensate for vulnerability and failure based on the Secret Sharing Scheme. In addition, we will confirm the effect of our method through experiments. Concerning security, we compare our method with the existing TinySec, which is the major security architecture of Wireless Sensor Networks.

Quantity-based event reliability protocols have been proposed for reliable event detection in wireless sensor networks. They support the event reliability by achieving the desired number of data packets successfully transmitted from sensor nodes sensing an event to a sink by controlling the transport process. However, since many data collisions and buffer overflows frequently happen due to data congestions on limited data delivery paths from an event to a sink, the quantity-based event reliability protocols are hard to achieve the desired number due to lost data packets. Thus, this letter proposes a Quality-based Event Reliability Protocol (QERP) utilizing a property that the data packets from sensor nodes have different Contribution Degree (CD) values for event detection according to their environmental conditions. QERP selects sensor nodes to forward their data packets according to CD, and differentially transports the data packets by CD-based buffer management and load balancing.

This paper proposes a lightweight, fast and efficient method for the detection of jamming attacks, interference, and other anomalies in electronic shelf label (ESL) systems and wireless sensor networks (WSNs) with periodic data transmission. The proposed method is based on the thresholding technique, which is applied to selected parameters of traffic and allows discrimination of random failures from anomalies and intrusions. It does not require the installation of additional hardware and does not create extra communication costs; its computational requirements are negligible, since it is based on statistical methods. Herein recommendations are provided for choosing a thresholds type. Extensive simulations, made by Castalia simulator for WSNs, show that the proposed method has superior accuracy compared to existing algorithms.

This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.

A novel distributed ranging method for wireless sensor networks (WSN) is proposed in this letter. Linear frequency modulation (LFM) waves are emitted from the two antenna elements equipped at the anchor node simultaneously to create an interference field. Through the frequency measurement of local RSSI (Received Signal Strength Indication) signal, the horizontal distance from the anchor node can be estimated independently at each sensor. Analysis and simulation results demonstrate the effectiveness of our proposed method.

The AODV routing protocol, which is simple and efficient, is often used in wireless sensor networks to transmit data. The AODV routing protocol constructs a path from the source node, which detects the target, to the sink node. Whenever the target moves, the path will be reconstructed and the RREQ packet will be broadcasted to flood the wireless sensor network. The localization repair routing protocol sets up a reconstruction area and restricts the broadcast of the RREQ packet to that area to avoid broadcast storm. However, this method cannot reconstruct the path once the target moves out of the reconstruction area. In this paper, we propose a lightweight routing protocol for mobile target detection. When the path breaks because of the movement of the target, the nodes can repair the path effectively using the presented routing information to achieve the lightweight effect.

Reliable data transmission is desirable in wireless sensor networks due to the high packet loss rate during multi-hop transmissions. To reliably transmit data for event-driven applications, packet loss recovery mechanism is needed. For loss recovery, sensor nodes need to keep packets in their buffers until transmissions successfully complete. However, since sensor nodes have limited memory, packets cannot be buffered for a long period of time. This letter proposes an efficient buffer management technique that caches data packets for appropriate amount of time to minimize the resource requirements and at the same time provide reliable data transmission among sensor nodes.

In clustered sensor networks, because CHs (Cluster Heads) are the collection points of data, they are likely to be compromise targets of attackers. So, they need to be changed through a CH election scheme as frequently as possible. Besides, because the compromised nodes must try to become a CH, a CH election scheme should prevent them from being a CH. This paper presents a secure CH election scheme for clustered sensor networks, which changes the CH role nodes securely by excluding the compromised nodes from CH candidates. In the proposed scheme, each node gives marks for behavior of all other nodes in the same CH election region and exchanges the mark list with them. Then, each node computes the average marks for all nodes in the region, and nodes whose average mark is less than a specific threshold are excluded from CH candidates. A CH is elected among the remaining candidates. Simulation results show that our scheme provides strong resilience against misbehavior of compromised nodes and reduces energy consumption of nodes. Another simulation results show that our scheme well operates in the environment where some packets are often lost.

In wireless sensor networks (WSNs), geographic routing algorithms can enhance the network capacity. However, in real WSNs, it is difficult for each node to know its physical location accurately. Geographic routing with location errors may produce serious problems such as disconnected links and data transmission delays. In this letter, we present an efficient location error compensation algorithm for the geographic routing. The proposed algorithm efficiently detects and corrects the location errors and significantly enhances the network performance of geographic routing in the presence of location errors.