Itamar Elhanany

An energy-efficient QoS-aware media access control protocol for wireless sensor networks

We present an innovative MAC protocol (Q-MAC) that minimizes the energy consumption in multi-hop wireless sensor networks (WSNs) and provides quality of service (QoS) by differentiating network services based on priority levels. The priority levels reflect application priority and the state of system resources, namely residual energy and queue occupancies. The Q-MAC utilizes both intra-node and inter-node arbitration. The intra-node packet scheduling is a multiple queuing architecture with packet classification and weighted arbitration. We also introduce the power conservation MACAW (PC-MACAW) - a power-aware scheduling mechanism that, together with the loosely prioritized random access (LPRA) algorithm, govern the inter-node scheduling. Performance evaluation are conducted between Q-MAC and S-MAC with respect to two performance metrics: energy consumption and average latency. Simulation results indicate that the performance of the Q-MAC is comparable to that of the S-MAC in non-prioritized traffic scenarios; when packets with different priorities are present, Q-MAC supiors in average latency differentiation between the classes of service, while maintaining the same energy level as that of S-MAC

A Novel Signal-Scheduling Algorithm With Quality-of-Service Provisioning for an Isolated Intersection

There have been countless efforts directed toward efficiently controlling the flow of vehicular traffic through an intersection. This paper describes an algorithm designed for the signal control problem that employs concepts drawn from the field of packet switching in computer networks. The novel method proposed utilizes a maximal weight matching algorithm to minimize the queue sizes at each approach, yielding significantly lower average vehicle delay through the intersection. Of particular interest are scenarios in which differentiated services are offered to vehicle classes with differing priorities. Lyapunov function-based analysis is provided, deriving the conditions under which the system is guaranteed to be stable. The algorithm is compared to an optimized fixed-time controller and a vehicle-actuated controller using the VISSIM traffic simulation environment. Simulation results demonstrate the performance gain obtained when using the proposed scheme, particularly in the scenario in which vehicle routes are unequally distributed, and multiple classes of service are desired.

Revisiting public-key cryptography for wireless sensor networks

The lack of a fixed infrastructure and the ad hoc nature of wireless sensor networks deployments suggest that the ability to encrypt and decrypt confidential data among arbitrary sensor nodes while enabling undisputed authentication of all parties will be a fundamental prerequisite for achieving security. To do this, nodes must be able to establish a secret key and know who their counterparts are. Thus, it becomes highly desirable to have a secure and efficient distribution mechanism that allows simple key generation for large-scale sensor networks while facilitating all the necessary authentications.

The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.

The Network Processing Forum switch fabric benchmark specifications: an overview

The Network Processing Forum chartered a fabric benchmarking task group to establish a set of switch fabric benchmark specifications that allows the characterization of a wide range of switch fabrics for diverse networking applications. A unique characteristic of the benchmarks is their ability to produce comparable performance results for different switch fabrics, regardless of their underlying architecture and technology. This article provides an overview of the NPF fabric benchmark specifications by describing the various topics addressed by the standard as well as their potential impact.

Robust image registration based on feedforward neural networks

A novel approach to accurate and robust image registration using feedforward neural networks is presented. Common registration schemes utilize some form of similarity measures in order to evaluate affine transformation parameters. In the proposed scheme, feedforward neural networks are employed as a means of providing translation, rotation and scaling parameters with respect to reference and observed image sets. Discrete cosine transform (DCT) features are extracted as inputs to the network. Experimental results with several deformed and noisy images indicate that the proposed algorithm is both accurate and remarkably robust to diverse noisy conditions.

A stable longest queue first signal scheduling algorithm for an isolated intersection

There have been countless efforts directed toward efficiently controlling the flow of traffic through an intersection. This paper describes an algorithm designed for the signal control problem that employs concepts drawn from the field of computer networking. The novel method proposed utilizes a maximal weight matching algorithm to minimize the queue sizes at each approach, yielding significantly lower average vehicle delay through the intersection. Lyapunov function-based analysis is provided, deriving the conditions under which the system is guaranteed to be stable. The algorithm is compared to an optimized fixed time controller using the VISSIM traffic simulation environment. Simulation results clearly demonstrate the performance gain obtained when using the proposed scheme, particularly in the presence of the non-uniform traffic scenario proposed.

DISA: a robust scheduling algorithm for scalable crosspoint-based switch fabrics

This paper presents and analyzes a high-performance, robust, and scalable scheduling algorithm for input-queued switches called distributed sequential allocation (DISA). In contrast to pointer-based arbitration schemes, the proposed algorithm is based on a synchronized output reservation process, whereby each input selects a designated output while taking into consideration both local transmission requests and the availability of global resources. The distinctiveness of the algorithm lies in its ability to offer high performance when multiple cells are transmitted within each switching interval. Relaxed switching-time requirements allow for the incorporation of commercially available crosspoint switches. The result is a pragmatic and scalable solution for high port-density switching platforms. The efficiency of the scheme and its robustness in the presence of admissible traffic, without the need for speedup, is established through analysis and computer simulations. Performance results are shown for various traffic scenarios including nonuniform destination distribution, correlated arrivals and multiple classes of service.

A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent

This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algorithm, whereby the sensitivity set of each neuron is reduced to weights associated with either its input or output links. This yields a reduced storage and computational complexity of O(N2). Stochastic meta descent (SMD), an adaptive step size scheme for stochastic gradient-descent problems, is employed as means of incorporating curvature information in order to substantially accelerate the learning process. We also introduce a clustered version of our algorithm to further improve its scalability attributes. Despite the dramatic reduction in resource requirements, it is shown through simulation results that the approach outperforms regular RTRL by almost an order of magnitude. Moreover, the scheme lends itself to parallel hardware realization by virtue of the localized property that is inherent to the learning framework.

Packet scheduling in next-generation multiterabit networks

The infrastructure required to govern Internet traffic volume, which doubles every six months, consists of two complementary elements: fast point-to-point links and high-capacity switches and routers. Dense wavelength division multiplexing (DWDM) technology, which permits transmission of several wavelengths over the same optical media, will enable optical point-to-point links to achieve an estimated 10 terabits per second by 2008. However, the rapid growth of Internet traffic coupled with the availability of fast optical links threatens to cause a bottleneck at the switches and routers.