Event-driven wireless sensor networks (WSNs) usually operate under light traffic load. However, when an event is detected, a large number of packets may be generated. A MAC protocol designed for this kind of WSNs should be able to swiftly adapt to the two conditions. Most WSN MAC protocols are optimized for light traffic for the energy efficiency consideration. In this paper, we propose a novel receiver-centric MAC protocol called RC-MAC that seamlessly integrates duty cycling and receiver-centric scheduling, providing high throughput without sacrificing the energy efficiency. To handle bursty traffic triggered by an event, RC-MAC takes advantage of the underlying data gathering tree structure of WSNs and the multichannel technique supported by current IEEE 802.15.4 RF transceivers to assist scheduling of medium access. The throughput is improved in two phases with receiver-centric medium access scheduling and distributed channel assignment. First, on a data gathering tree, a receiver is able to coordinate the medium access of multiple senders so as to reduce collisions and achieve high throughput. Second, different receivers coordinate their senders in different channels and the throughput is further improved by allowing parallel data gathering. Observing packet processing time on low cost sensor nodes, we design a scheduling pattern that ensures fairness between source nodes without sacrificing the throughput. We evaluate the performance of our RC-MAC through measurements of an implementation in TinyOS on TelosB motes and extensive ns-2 simulations. Compared with contention-based and scheduling-based MAC protocols, we show that the throughput and the fairness under heavy traffic load are significantly improved by the receiver-centric scheduling. Due to the high throughput, the energy efficiency is also improved.

Greedy forwarding is a simple yet efficient technique employed by many routing protocols. It is ideal to realize point-to-point routing in wireless sensor networks because packets can be delivered by only maintaining a small set of neighbors' information regardless of network size. It has been successfully employed by geographic routing, which assumes that a packet can be moved closer to the destination in the network topology if it is forwarded geographically closer to the destination in the physical space. This assumption, however, may lead packets to the local minimum where no neighbors of the sender are closer to the destination or low-quality routes that comprise long distance hops of low packet reception ratio. To address the local minimum problem, we propose a topology aware routing (TAR) protocol that efficiently encodes a network topology into a low-dimensional virtual coordinate space where hop distances between pairwise nodes are preserved. Based on precise hop distance comparison, TAR can assist greedy forwarding to find the right neighbor that is one hop closer to the destination and achieve high success ratio of packet delivery without location information. Further, we improve the routing quality by embedding a network topology based on the metric of expected transmission count (ETX). ETX embedding accurately encodes both a network's topological structure and channel quality to nodes' small size virtual coordinates, which helps greedy forwarding to guide a packet along the optimal path that has the fewest number of transmissions. We evaluate our approaches through both simulations and experiments, showing that routing performance are improved in terms of routing success ratio and routing cost.

Wireless sensor networks usually operate under light traffic loads. However, when an event is detected, a large volume of data may be generated and delivered to the sink. The demand for simultaneous data transmission may cause severe channel collision and thus decrease communication throughput in contention-based medium access control (MAC) protocols. In this paper, we introduce a novel receiver-centric data transmission paradigm, which takes advantage of the tree structure that is naturally formed in data collection of a sensor network to assist scheduling of channel access. On the tree structure, a receiver is able to coordinate its multiple senders' channel access so as to reduce channel contention and consequently improve communication throughput. The protocol seamlessly integrates scheduling with contention-based medium access control. In addition, to ensure reliable data transmission, we propose a sequence-based lost packet recovery scheme in a hop-by-hop recovery pattern, which could further improve communication throughput by reducing control overhead. We present the performance of our receiver-centric MAC protocol through measurements of an implementation in TinyOS on TelosB motes and extend the evaluation through ns-2 simulations. Compared with B-MAC and RI-MAC, we show the benefits of improving throughput and fairness through receiver-centric scheduling under heavy traffic loads.

This paper presents an adaptive partitioning scheme of sensor networks for node scheduling and topology control with the aim of reducing energy consumption. Our scheme partitions sensors into groups such that a connected backbone network can be maintained by keeping only one arbitrary node from each group in active status while putting others to sleep. Unlike previous approaches that partition nodes geographically, our scheme is based on the measured connectivity between pairwise nodes and does not depend on nodes' locations. In this paper, we formulate node scheduling with topology control as a constrained optimal graph partition problem, which is NP-hard, and propose a Connectivity-based Partition Approach (CPA), which is a distributed heuristic algorithm, to approximate a good solution. We also propose a probability-based CPA algorithm to further save energy. CPA can ensure K-vertex connectivity of the backbone network, which achieves the trade-off between saving energy and preserving network quality. Moreover, simulation results show that CPA outperforms other approaches in complex environments where the ideal radio propagation model does not hold.

In sensor network localization, multihop based approaches have been proposed to approximate the shortest paths to Euclidean distances between pairwise sensors. A good approximation can be achieved when sensors are densely deployed in a convex area, where the shortest paths are close to straight lines connecting pairwise sensors. However, in a concave network, the shortest paths may deviate far away from straight lines, which leads to erroneous distance estimation and inaccurate localization results. To solve this problem, we propose an improved multihop algorithm that can recognize and filter out the erroneous distance estimation, and therefore achieve accurate localization results even in a concave network.

A flooding-based search mechanism is often used in unstructured P2P systems. Although a flooding-based search mechanism is simple and easy to implement, it is vulnerable to overlay distributed denial-of-service (DDoS) attacks. Most previous security techniques protect networks from network-layer DDoS attacks, but cannot be applied to overlay DDoS attacks. Overlay flooding-based DDoS attacks can be more damaging in that a small number of messages are inherently propagated to consume a large amount of bandwidth and computation resources. We propose a distributed and scalable method, DD-POLICE, to detect malicious nodes in order to defend P2P systems from overlay flooding-based DDoS attacks. We show the effectiveness of DD-POLICE by comprehensive simulation studies. We believe that deploying DD-POLICE will make P2P systems more scalable and robust.

In this paper, we reveal the inherent tradeoff between the quality of routing performance and the size of routing states in wireless networks. We suggest that the key approach to an optimal routing design is how toefficientlyencode a network topology into small dimensional coordinates from which hop count distances between pairwise sensors can beaccuratelyrecovered. Based on the precisely hop count distance comparison, our proposed topology aware routing can assist the greedy forwarding to find the right neighbor that is one hop closer to the destination, and therefore achieve high success rate of packet delivery. The intensive performance evaluation shows that the topology aware routing can achieve routing performance comparable to the shortest path routing while preserving the routing states as small as location aware routing. Particularly, high routing success rate can be achieved in both concave environments where voids are presented and dynamic environments where nodes crash frequently.

Although the original intent of the peer-to-peer (P2P) concept is to treat each participant equally, heterogeneity widely exists in deployed P2P networks. Peers are different from each other in many aspects, such as bandwidth, CPU power, and storage capacity. Some approaches have been proposed to take advantage of the query forwarding heterogeneity such that the high bandwidth of powerful nodes can be fully utilized to maximize the system capacity. In this paper, we suggest using the query answering heterogeneity to directly improve the search efficiency of P2P networks. In our proposed differentiated search (DiffSearch) algorithm, the peers with high query answering capabilities will have higher priority to be queried. Because the query answering capabilities are extremely unbalanced among peers, a high query success rate can be achieved by querying only a small portion of a network. The search traffic is significantly reduced due to the shrunken search space. Our trace analysis and simulation show that the DiffSearch algorithm can save up to 60 percent of search traffic

Unstructured peer-to-peer networks have become a very popular method for content distribution in the past few years. By not enforcing strict rules on the network's topology or content location, such networks can be created quickly and easily. Unfortunately, because of the unstructured nature of these networks, in order to find content, query messages are flooded to nodes in the network, which results in a large amount of traffic. This work borrows the technique of association analysis from the data mining community and extends it to intelligently forward queries through the network. Because only a small subset of a node's neighbors are forwarded queries, the number of times those queries are propagated is also reduced, which results in considerably less network traffic. These savings enable the networks to scale to much larger sizes, which allows for more content to be shared and more redundancy to be added to the system, as well as allowing more users to take advantage of such networks

Abstract — In sensor network localization, multihop based approaches were proposed to approximate the shortest paths to Euclidean distances between pairwise sensors. A good approximation can be achieved when sensors are densely deployed in a convex area, where the shortest paths are close to straight lines connecting pairwise sensors. However, in a concave network, the shortest paths may deviate far away from straight lines, which leads to erroneous distance estimation and inaccurate localization results. In this paper, we propose an improved multihop algorithm which can recognize and filter out the erroneous distance estimation, and therefore achieve accurate localization results even in a concave network. I.

In sensor localization, ultrasound based distance measurements will have large errors if line-of-sight paths are blocked between pairwise sensors. Because these outliers, once mixed together with other correct distance measurements, are difficult for localization algorithms to identify, we propose to exclude the outliers in the first step of distance measurement. Although the distance between pairwise sensors measured by ultrasound can have multiple values due to the multipath effect, our experiments find that a sensor's incorrect position, estimated from the distance measurement along a reflected path instead of a straight line, is always mirrored to the sensor's correct position. Based on this phenomena, we propose to use mobile beacons to measure the distance between pairwise sensors from multiple perspectives and filter incorrect values through a statistical approach. Our performance evaluation shows that the proposed algorithm can achieve better localization results than previous approaches in an indoor environment where multipath effects cannot be avoided

Peer-to-peer networks are widely criticized for their inefficient flooding search mechanism. Distributed hash table (DHT) algorithms have been proposed to improve the search efficiency by mapping the index of a file to a unique peer based on predefined hash functions. However, the tight coupling between indices and hosting peers incurs high maintenance cost in a highly dynamic network. To properly balance the tradeoff between the costs of indexing and searching, we propose the distributed caching and adaptive search (DiCAS) algorithm, where indices are passively cached in a group of peers based on a predefined hash function. Guided by the same function, adaptive search selectively forwards queries to "matched" peers with a high probability of caching the desired indices. The search cost is reduced due to shrunk searching space. Different from the DHT solutions, distributed caching loosely maps the index of a file to a group of peers in a passive fashion, which saves the cost of updating indices. Our simulation study shows that the DiCAS protocol can significantly reduce the network search traffic with the help of small cache space contributed by each individual peer

Although the original intent of the peer-to-peer (P2P) concept is to treat each participant equally, heterogeneity widely exists in deployed P2P networks. In this paper, we suggest to improve the search efficiency of P2P network by utilizing the query answering heterogeneity. Our proposed differentiated search (DiffSearch) algorithm can evolve an unstructured P2P network to a two-tier hierarchical structure, where peers with high query answering capabilities are grouped in the first tier, which has higher priority to be queried than the second tier. Because the query answering capability is extremely unbalanced among peers, a high query success ratio can be achieved by querying only a small portion of the network. The search traffic is dramatically reduced due to the shrunken search space. Our trace analysis and simulation show that the DiffSearch algorithm can save up to 60% of search traffic.

Security is one of the top concerns when sensors are deployed in hostile environments for military applications. Attacks on sensor nodes can be categorized into two types: attacks through radio signals to alter the functionalities of sensors and physical attacks; which may completely damage sensors. We show that the former is easier to launch and more disguised, thus more hazardous. The layered framework proposed in this paper is specially designed to defend against the first type of attacks. Different from precious reputation-based approaches or data mining technologies which usually incur large communication and computation overhead, our solution only involves localized computation which is less intensive, thus can be implemented on-board with little burden on current MICA2 platforms. Besides identifying malicious nodes, our solution can also recover the normal functionalities of sensors, which have been altered by malicious radio signals

To improve the scalability of Gnutella-like unstructured peer-to-peer (P2P) networks, a uniform index caching (UIC) mechanism was suggested in some earlier work. In UIC, query results are cached in all peers along the inverse query path such that the same query of other peers can be replied from their nearby-cached results. However, our experiments show that the UIC method causes a large amount of duplicated and unnecessary caching of items among neighboring peers. Aiming at improving the search efficiency, we propose a distributed caching mechanism, which distributes the cache results among neighboring peers. Furthermore, based on the distributed caching mechanism, an adaptive search approach is built which selectively forwards the query to the peers with a high probability of providing the desired cache results. All the enhancements above are defined in a protocol called distributed caching and adaptive search (DiCAS). In the DiCAS enhanced Gnutella network, all the peers are logically divided into multiple layers, with the character that all the peers in the same layer have the same group ID. The query flooding is restricted in one layer with the matched group ID. Our simulation study shows that, with the help of the index caching and search space division, the DiCAS protocol can significantly reduce the network search traffic in unstructured P2P systems without degrading query success rate.