15232013
An Adaptive Reputation-based Trust Framework for Peer-to-Peer Applications
In distributed P2P environments, peers (i.e., users) often have to request the services from some unfamiliar peers (i.e., resources) that could be altruistic, selfish, or even malicious. To motivate selfish peers to cooperate and minimize the risk from malicious peers, we propose an adaptive reputation-based trust framework for peer-to-peer applications. In this framework, we define a quantifiable metric trust that is calculated from the user's own view as well as other peers' view (as references) on the reputation of a peer (resource). It can be used to quantify the trustworthiness of peers and provide a measurable and trustable way of resource scheduling/selection and access control for peer-to-peer applications. We assume economic resources compete with each other to maximize their profit and design a number of strategies, for resources to determine their price. The simulation results show that the framework supports economic resources to achieve long-term high user satisfaction, differentiates malicious nodes from normal ones and encourages the resources to provide high-quality services
1959706
A key pre-distribution scheme using deployment knowledge for wireless sensor networks
Sensor networks pose security and privacy challenges. One challenge is how to bootstrap secure communications among nodes. Several key pre-distribution schemes have been proposed, however, they either have a high memory requirement for large networks or need a large transmission range to achieve the desired connectivity. In this paper, we propose a novel key pre-distribution scheme using deployment knowledge. In our scheme, sensor field is divided into multiple hexagonal grids and nodes are divided into groups, each of which is deployed into a grid. By using deployment knowledge, we can drastically reduce the number of potential groups from which neighbors of each node may come. Thus, a pair-wise key can be generated efficiently for each pair of neighbors. Compared to existing schemes, our scheme achieves a high connectivity with a lower memory requirement and a smaller transmission range and outperforms others in resilience against node capture attacks.
46151699
A Dynamic En-Route Scheme for Filtering False Data Injection in Wireless Sensor Networks
6970027
A Dynamic En-Route Scheme for Filtering False Data Injection in Wireless Sensor Networks
In this paper, we propose a dynamic en-route filtering scheme for false data injection attacks in wireless sensor networks. In sensor networks, adversaries can inject false data reports containing bogus sensor readings or nonexistent events from compromised nodes. Such attacks may not only cause false alarms, but also drain out the limited energy of sensor nodes. Several existing schemes for filtering false reports either cannot deal with dynamic topology of sensor networks or have limited filtering capacity. In our scheme, a legitimate report is endorsed by multiple sensing nodes using their own authentication keys generated from one-way hash chains. Cluster head uses Hill Climbing approach to disseminate the authentication keys of sensing nodes to the forwarding nodes along multiple paths toward the base station. Hill Climbing guarantees that the forwarding nodes closer to a cluster hold more authentication keys for the cluster than those nodes farther from it do, hence, the number of keys held by each forwarding node can be balanced. In filtering phase, each forwarding node validates the authenticity of the reports and drops those false ones. Compared to existing schemes, our scheme can better deal with dynamic topology of sensor networks. Analytical and simulation results show that our scheme drops false reports earlier even with a lower memory requirement and tolerates more compromised nodes. Our scheme also outperforms others in term of energy efficiency, especially for large sensor networks.
17105028
Performance and power analysis of globally asynchronous locally synchronous multiprocessor systems
This paper investigates the performance and power dissipation of globally asynchronous locally synchronous (GALS) multi-processor systems. We show that communication loops are a source of significant throughput degradation in communications links and that there is no degradation whatsoever under certain conditions for one-way links, and that it is possible to design GALS multiprocessors without this performance penalty. Independent clock domains and unbalanced computation in the GALS multiprocessor allow scaling of the clock frequency and supply voltage to achieve high energy efficiency. The synchronization overhead between independent clock domains results in a less than 1% performance reduction compared to a globally synchronous system over a number of DSP and numerical applications. Clock and voltage scaling can achieve an approximately 40% power savings with no reduction of performance. These results compare favorably with the 25% power savings and more than 10% performance reduction reported for GALS uniprocessors
3757616
Hamilton cycles in 1-tough triangle-free graphs
A graph G is called triangle-free if G has no induced K3 as a subgraph. We set σ3=min{∑i=13d(vi)|{v1,v2,v3} is an independent set of vertices in G}. In this paper, we show that if G is a 1-tough and triangle-free graph of order n with n⩽σ3, then G is hamiltonian.
35376903
Robust beamformer design by power minimization and its unconstrained partitioned implementation
A robust array beamformer design method by power minimization and its unconstrained partition implementation is proposed in this paper. An orthogonal blocking matrix is obtained through the proposed method. The new blocking matrix ensures that a desired look-direction response of the processor over a frequency band of interest can be closely approximated. Furthermore, if the spectrum of the target signal is known a priori, such as in microphone array application where the statistical property of speech is known, the new method may use fewer/less degree of freedom. This new method also provide a theoretical support for the derivation of the blocking matrix through array calibration. Simulation results show that the effectiveness of the proposed method.
9807820
Norm and coefficient constraints for robust adaptive beamforming
Norm-constrained and coefficient-constrained adaptive filters are often used in robust adaptive beamforming to mitigate the target-signal cancellation problem caused by DOA (direction of arrival) mismatch. The norm and coefficient constraints are usually selected numerically based on computer simulations or real-time experiments, which is not enough for theoretical analysis that requires explicit mathematical expressions. This paper analytically derives these constraints using the Taylor series expansion of the array correlation matrix. The constraints that are expressed in terms of maximal DOA mismatch agree well with the simulation results, and most importantly they are quite useful in practical beamformer design and performance analysis.
16105685
A Hybrid Learning Approach for TV Program Personalization
The rapid growth of communication technologies and the invention of set-top-box (STB) and personal digital recorder (PDR) have enabled today’s television to receive and store tremendous programs. The abundance of TV programs precipitates a need for personalization tools to help people obtain programs that they really want to watch. User preference learning plays an important role in TV program personalization. In this paper, we introduce a hybrid user preference learning approach for TV program personalization. The learning architecture is designed to integrate multiple learning sources for preference learning, which are explicit input/modification, user viewing history, and user real-time feedback. Among those, learning from user viewing history and learning from user real-time feedback are described in detail. The experimental results proved that the hybrid learning approach outperforms the learning method merely adopting user real-time feedback.