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Ensuring anonymity in wireless and hoc networks is a major security goal. Using traffic analysis, the attacker can compromise the network functionality by correlating data flow patterns to event locations/active areas. In this paper we present a novel Scalable Anonymous Protocol that hides the location of nodes and obscure the correlation between event zones and data flow from snooping adversaries. We quantify the anonymity strength of our protocol by introducing a new anonymity metric: Degree of Exposure Index. Our protocol is designed to offer flexible tradeoffs between degree of anonymity and communication-delay overhead. [ABSTRACT FROM AUTHOR]

We propose to use IEEE 802.22 networks as a natural interconnection between energy-constrained networks, such as sensor networks, and the Internet. In this interconnection scenario, we propose Activecast, broadcast designed as a continuation of the IEEE 802.22 broadcast on sensor networks. Activecast effectively transmits a query to all active sensors in the network. Activecast minimizes the number of retransmitted messages while maintaining high reachability. Activecast requires minimum communication overhead, yet performs very well in the presence of various environmental constrains. Activecast can also be integrated to any sleep based sensor protocol, as it does not make any assumptions on the underlying wake up scheduling protocol and wake up times/durations of the sensors. We study the properties of Activecast by analysis and simulations while also considering irregular radio coverage of sensors. [ABSTRACT FROM AUTHOR]

In this paper we present Clustering Protocol for Sensor networks (CPS). Clustering techniques are used by different protocols and applications to increase scalability and reduce delays in sensor networks. Examples include routing protocols, and applications requiring efficient data aggregation. Our approach is based on the Covering Problem that aims at covering an area with minimum number of circular disks. CPS is a lightweight protocol that does not require any neighborhood information and imposes low communication overhead. We present simulation results to show the efficiency of CPS in both ideal cases and randomly distributed networks. Moreover, CPS is scalable with respect to density and network size. [ABSTRACT FROM AUTHOR]

We present Delay-Energy Aware Routing (DEAP) a novel protocol for heterogeneous wireless ad hoc networks. DEAP is a crosslayer scheme that: first, manages adaptively the energy control by controlling the wakeup cycle of sensors based on the experienced packet delay; and second, rout packet in each hoc by distributing the load a group of neighboring nodes. The primary result of DEAP is that it enables a flexible and wide range of tradeoffs between the packet delay and the energy consumption. Therefore, DEAP supports delay sensitive applications of heterogeneous networks that include sensors and actors. DEAP is scalable to the change in network size, node type, node density and topology. DEAP accommodates seamlessly such network changes, including the presence of actors in heterogeneous sensor networks. Indeed, while DEAP does not count on actors, it takes advantage of them, and uses their resources when possible, thus reducing the energy consumption of sensor nodes. Through analysis and simulation evaluations, we show that DEAP improves the packet delay and network lifetime compared to other protocols. [ABSTRACT FROM AUTHOR]

We present Geometric Broadcast for Heterogeneous Sensor Networks (GBS), a novel broadcasting protocol for heterogeneous wireless sensor and actor networks. While broadcasting is a very energy expensive protocol, it is also widely used as a building block for a variety of other network layer protocols. Therefore, reducing the energy consumption by optimizing broadcasting is a major improvement in heterogenous sensor networking. GBS is a distributed algorithm where nodes make local decisions on whether to transmit based on a geometric approach. GBS does not need any neighborhood information and imposes very low communication overhead. GBS is scalable to the change in network size, node type, node density and topology. Furthermore it accommodates seamlessly such network changes, including the presence of actors in heterogeneous sensor networks. Indeed, GBS takes advantage of actor nodes, and uses their resources when possible, thus reducing the energy consumption by sensor nodes. Through simulation evaluations, we show that GBS is very scalable and its performance is improved by the presence of actors. At the best of our knowledge, GBS is the first broadcast protocol designed specifically for heterogeneous sensor and actor networks. [ABSTRACT FROM AUTHOR]

Sensor networks usually operate under very severe energy restrictions. Therefore, sensor communications should consume the minimum possible amount of energy. While broadcasting is a very energy-expensive protocol, it is also widely used as a building block for a variety of other network layer protocols. Therefore, reducing the energy consumption by optimizing broadcasting is a major improvement in sensor networking. In this paper, we propose an optimized Broadcast Protocol for Sensor networks (BPS). The major novelty of BPS is its adaptive-geometric approach that enables considerable reduction of retransmissions by maximizing each hop length. BPS adapts itself and gets the best out of existing radio conditions. In BPS, nodes do not need any neighborhood information, which leads to low communication and memory overhead. We analyze the worst-case scenario for BPS and show that the number of transmissions in such a scenario is a constant multiple of those required in the ideal case. Our simulation results show that BPS is very scalable with respect to network density. BPS is also resilient to transmission errors. [ABSTRACT FROM AUTHOR]