Fikret Sivrikaya

Time synchronization in sensor networks: a survey

Time synchronization is an important issue in multihop ad hoc wireless networks such as sensor networks. Many applications of sensor networks need local clocks of sensor nodes to be synchronized, requiring various degrees of precision. Some intrinsic properties of sensor networks, such as limited resources of energy, storage, computation, and bandwidth, combined with potentially high density of nodes make traditional synchronization methods unsuitable for these networks. Hence, there has been an increasing research focus on designing synchronization algorithms specifically for sensor networks. This article reviews the time synchronization problem and the need for synchronization in sensor networks, then presents in detail the basic synchronization methods explicitly designed and proposed for sensor networks.

A Combinatorial Approach to Measuring Anonymity

In this paper we define a new metric for quantifying the degree of anonymity collectively afforded to users of an anonymous communication system. We show how our metric, based on the permanent of a matrix, can be useful in evaluating the amount of information needed by an observer to reveal the communication pattern as a whole. We also show how our model can be extended to include probabilistic information learned by an attacker about possible sender-recipient relationships. Our work is intended to serve as a complementary tool to existing information-theoretic metrics, which typically consider the anonymity of the system from the perspective of a single user or message.

Contention-free MAC protocols for wireless sensor networks

A MAC protocol specifies how nodes in a sensor network access a shared communication channel. Desired properties of such MAC protocol are: it should be distributed and contention-free (avoid collisions); it should self-stabilize to changes in the network (such as arrival of new nodes), and these changes should be contained, i.e., affect only the nodes in the vicinity of the change; it should not assume that nodes have a global time reference, i.e., nodes may not be time-synchronized. We give the first MAC protocols that satisfy all of these requirements, i.e., we give distributed, contention-free, self-stabilizing MAC protocols which do not assume a global time reference. Our protocols self-stabilize from an arbitrary initial state, and if the network changes the changes are contained and the protocol adjusts to the local topology of the network. The communication complexity, number and size of messages, for the protocol to stabilize is small (logarithmic in network size).

Distributed Attack Graph Generation

Attack graphs show possible paths that an attacker can use to intrude into a target network and gain privileges through series of vulnerability exploits. The computation of attack graphs suffers from the state explosion problem occurring most notably when the number of vulnerabilities in the target network grows large. Parallel computation of attack graphs can be utilized to attenuate this problem. When employed in online network security evaluation, the computation of attack graphs can be triggered with the correlated intrusion alerts received from sensors scattered throughout the target network. In such cases, distributed computation of attack graphs becomes valuable. This article introduces a parallel and distributed memory-based algorithm that builds vulnerability-based attack graphs on a distributed multi-agent platform. A virtual shared memory abstraction is proposed to be used over such a platform, whose memory pages are initialized by partitioning the network reachability information. We demonstrate the feasibility of parallel distributed computation of attack graphs and show that even a small degree of parallelism can effectively speed up the generation process as the problem size grows. We also introduce a rich attack template and network model in order to form chains of vulnerability exploits in attack graphs more precisely.

Cooperative game theoretic approach to integrated bandwidth sharing and allocation

The current trend in wireless communication networks involves the integration of different wireless access technologies into a single operator network. The possible leveraging of high deployment costs, and the possibility to increase revenue have also introduced the concept of network sharing between different operators. The problem of optimal allocation of bandwidth to multimedia applications over different wireless access networks, is augmented with the possibility of using the bandwidth of other operators who are willing to share bandwidth.We formulate the allocation of bandwidth within the operator network and distribution of excess bandwidth among operators as cooperative bargaining games. We provide distribution and allocation rules based on the Kalai-Smorodinsky Solution, and provide bandwidth offer algorithms based on these rules. We compare this integrated approach with the service and capacity based approaches in the literature.

Joint problem of power optimal connectivity and coverage in wireless sensor networks

This work considers a multi-hop sensor network and addresses the problem of minimizing power consumption in each sensor node locally while ensuring two global (i.e., network wide) properties: (i) communication connectivity, and (ii) sensing coverage. A sensor node saves energy by suspending its sensing and communication activities according to a Markovian stochastic process. We show that a power level to induce a coverage radius

Stochastic Routing in Wireless Sensor Networks

\frac{w(n)}{n}

Contention-free MAC protocols for asynchronous wireless sensor networks

is sufficient for connectivity provided that w(n)→∞. The paper presents a Markov model and its solution for steady state distributions to determine the operation of a single node. Given the steady state probabilities, we construct a non-linear optimization problem to minimize the power consumption. Simulation studies to examine the collective behavior of large number of sensor nodes produce results that are predicted by the analytical model.