Abstract — Although many energy efficient/conserving routing protocols have been proposed for wireless sensor networks, the concentration of data traffic towards a small number of base stations remains a major threat to the network lifetime. The main reason is that the sensor nodes located near a base station have to relay data for a large part of the network and thus deplete their batteries very quickly. The solution we propose in this paper suggests that the base station be mobile; in this way, the nodes located close to it change over time. Data collection protocols can then be optimized by taking both base station mobility and multi-hop routing into account. We first study the former, and conclude that the best mobility strategy consists in following the periphery of the network (we assume that the sensors are deployed within a circle). We then consider jointly mobility and routing algorithms in this case, and show that a better routing strategy uses a combination of round routes and short paths. We provide a detailed analytical model for each of our statements, and corroborate it with simulation results. We show that the obtained improvement in terms of network lifetime is in the order of 500%.

Abstract — We propose a new link metric called normalized advance (NADV) for geographic routing in multihop wireless networks. NADV selects neighbors with the optimal trade-off between proximity and link cost. Coupled with the local next hop decision in geographic routing, NADV provides an adaptive and efficient costaware routing strategy. Depending on the objective or message priority, applications can use the NADV framework to minimize various types of link cost. In this paper we present efficient methods for link cost estimation and perform detailed simulations in diverse scenarios. Our results show that NADV outperforms current schemes in many aspects: for example, in high noise environments with frequent packet losses, the use of NADV leads to 83 % higher delivery ratio. When compared to centralized routing, geographic routing using NADV finds paths whose cost is close to the optimum. Index Terms — System design, Simulations I.

As sensor-driven applications become increasingly integrated into our lives, issues related to sensor privacy will become increasingly important. Although many privacy-related issues can be addressed by security mechanisms, one sensor network privacy issue that cannot be adequately addressed by network security is confidentiality of the source sensor’s location. In this paper, we focus on protecting the source’s location by introducing suitable modifications to sensor routing protocols to make it difficult for an adversary to backtrack to the origin of the sensor communication. In particular, we focus on the class of flooding protocols. While developing and evaluating our privacy-aware routing protocols, we jointly consider issues of location-privacy as well as the amount of energy consumed by the sensor network. Motivated by the observations, we propose a flexible routing strategy, known as phantom routing, which protects the source’s location. Phantom routing is a two-stage routing scheme that first consists of a directed walk along a random direction, followed by routing from the phantom source to the sink. Our investigations have shown that phantom routing is a powerful technique for protecting the location of the source during sensor transmissions.

Underwater Sensor Networks (UWSNs) are significantly different from land-based sensor networks. In UWSNs, the new features: low bandwidth, high latency, high network dynamics, high error probability, and 3-dimensional space, bring big challenges to network protocol design. In this technical report, we tackle one fundamental problem in UWSNs: scalable and energy efficient routing. We propose a novel routing protocol, called vector-based forwarding (VBF) to address these new challenges. VBF is scalable and energy efficient. In VBF, no state information is required on the sensor nodes and only a small fraction of the nodes are involved in routing. Moreover, we develop a localized and distributed self-adaptation algorithm to enhance the performance of VBF. The self-adaptation algorithm allows the nodes to weigh the benefit to forward packets and reduce energy consumption by discarding the low benefit packets. We evaluate the performance of VBF through extensive simulations. Our experiment results show that for networks with small or medium node mobility (2 m/s-10 m/s), VBF can effectively accomplish the goals of energy efficiency, high success of data delivery and low end-to-end delay.

Abstract — One of the most notable challenges threatening the successful deployment of sensor systems is privacy. Although many privacy-related issues can be addressed by security mechanisms, one sensor network privacy issue that cannot be adequately addressed by network security is source-location privacy. Adversaries may use RF localization techniques to perform hop-by-hop traceback to the source sensor’s location. This paper provides a formal model for the source-location privacy problem in sensor networks and examines the privacy characteristics of different sensor routing protocols. We examine two popular classes of routing protocols: the class of flooding protocols, and the class of routing protocols involving only a single path from the source to the sink. While investigating the privacy performance of routing protocols, we considered the tradeoffs between location-privacy and energy consumption. We found that most of the current protocols cannot provide efficient source-location privacy while maintaining desirable system performance. In order to provide efficient and private sensor communications, we devised new techniques to enhance source-location privacy that augment these routing protocols. One of our strategies, a technique we have called phantom routing, has proven flexible and capable of protecting the source’s location, while not incurring a noticeable increase in energy overhead. Further, we examined the effect of source mobility on location privacy. We showed that, even with the natural privacy amplification resulting from source mobility, our phantom routing techniques yield improved source-location privacy relative to other routing methods. I.

Routing is one of the key challenges in sensor networks that directly affects the information throughput and energy expenditure. Geographic routing is the most scalable routing scheme for statically placed nodes in that it uses only a constant amount of per-node state regardless of network size. The location information needed for this scheme, however, is not easy to compute accurately using current localization algorithms. In this paper, we propose a novel logical coordinate framework that encodes connectivity information for routing purposes without the benefit of geographic knowledge, while retaining the constant-state advantage of geographic routing. In addition to efficiency in the absence of geographic knowledge, our scheme has two important advantages: (i) it improves robustness in the presence of voids compared to other logical coordinate frameworks, and (ii) it allows inferring bounds on route hop count from the logical coordinates of the source and destination nodes, which makes it a candidate for use in soft real-time systems. The scheme is evaluated in simulation demonstrating the advantages of the new protocol. 1.

Since sensor networks can be composed of a very large number of nodes, the developed protocols for these networks must be scalable. Moreover, these protocols must be designed to prolong the battery lifetime of the nodes. Typical existing routing techniques for ad hoc networks are known not to scale well. On the other hand, the so-called geographical routing algorithms are known to be scalable but their energy efficiency has never been extensively and comparatively studied. For this reason, a novel analytical framework is introduced. In a geographical routing algorithm, the packets are forwarded by a node to its neighbor based on their respective positions. The proposed framework allows to analyze the relationship between the energy efficiency of the routing tasks and the extension of the range of the topology knowledge for each node. The leading forwarding rules for geographical routing are compared in this framework, and the energy efficiency of each of them is studied. Moreover Partial Topology Knowledge Forwarding, a new forwarding scheme, is introduced. A wider topology knowledge can improve the energy efficiency of the routing tasks but can increase the cost of topology information due to signaling packets that each node must transmit and receive to acquire this information, especially in networks with high mobility. The problem of determining the optimal Knowledge Range for each node to make energy efficient geographical routing decisions is tackled by Integer Linear Programming. It is demonstrated that the problem is intrinsically localized, i.e., a limited knowledge of the topology is sufficient to take energy efficient forwarding decisions, and that the proposed forwarding scheme outperforms the others in typical application scenarios. For online solution of th...

MPI for Software Systems Abstract. The popularity of handheld devices has created a flurry of research activity into new protocols and applications that can handle and exploit the defining characteristic of this new environment – user mobility. In addition to mobility, another defining characteristic of mobile systems is user social interaction. This paper investigates how mobile systems could exploit people’s social interactions to improve these systems ’ performance and query hit rate. For this, we build a trace-driven simulator that enables us to re-create the behavior of mobile systems in a social environment. We use our simulator to study three diverse mobile systems: DTN routing protocols, firewalls preventing a worm infection, and a mobile P2P file-sharing system. In each of these three cases, we find that mobile systems can benefit substantially from exploiting social information. 1

We discuss how to automatically obtain the metric calibration of an ad-hoc network of cameras with no centralized processor. We model the set of uncalibrated cameras as nodes in a communication network, and propose a distributed algorithm in which each camera performs a local, robust bundle adjustment over the camera parameters and scene points of its neighbors in an overlay “vision graph”. We analyze the performance of the algorithm on both simulated and real data, and show that the distributed algorithm results in a fairer allocation of messages per node while achieving comparable calibration accuracy to centralized bundle adjustment.

Highly dynamic sensor networks, such as mobile robotic sensor networks, have been applied in various kinds of application scenarios such as real-time planet exploration and deep-ocean discovery. In these types of networks, mobility and energy management protocols change the connectivity among the neighboring nodes quickly. Traditional state-based protocols, designed for static and/or low-mobility networks, suffer excessive delay in updating their routing or neighborhood tables, leading to severe packet loss and communication delay in the highly dynamic situations. To provide robust and timely communication, we exploit the concept of Lazy-Binding to deal with the elevated network dynamics. Based on this concept and the knowledge of the node positions, we introduce Implicit Geographic Forwarding (IGF), a new protocol for highly dynamic sensor networks that is altogether state-free. We compare our work against several typical routing protocols in static, mobile and energy-conserving networks under a wide range of system and workload configurations. In the presence of mobility and other dynamics, IGF achieves as much as 10 times improvement in the delivery ratio and significant reduction in both the end-to-end delay and control overhead. In addition to extensive simulations, we also implement and evaluate the IGF protocol on the Berkeley mote platform. I.