6612620
Design techniques for sensor appliances: foundations and light compass case study
We propose the first systematic, sensor-centric approach for quantitative design of sensor network appliances. We demonstrate its use by designing light appliance devices and the associated middleware. We have developed five models which are required to make this problem tractable and to undertake the challenging task of designing light sensor appliances: i. physical world, ii. light sensor, iii. physical phenomenon, iv. appliance design, and v. computational model. With these models in place, we present the new design methodology that consists of two main steps: 1. a procedure for placement of individual sensors of the appliances, and 2. error minimization-based sensor data interpretation middleware. We have developed new optimization techniques for both tasks. A portable light sensor system was designed using the optimization intensive procedure, and its effectiveness demonstrated.
17876052
Probabilistic constructive optimization techniques
We have developed a new optimization paradigm for solving computationally intractable combinatorial optimization and synthesis problems. The technique, named probabilistic constructive, combines the advantages of both constructive and probabilistic optimization mechanisms. Since it is a constructive approach, it has a relatively short runtime and is amenable for the inclusion of insights through heuristic rules. The probabilistic nature facilitates a flexible tradeoff between runtime and the quality of solution, suitability for the superimposition of a variety of control strategies, and simplicity of implementation. After presenting the generic technique, we apply it to a generic NP-complete problem (maximum independent set) and a synthesis and compilation problem (sequential code covering). Extensive experimentation indicates that the new approach provides very attractive tradeoffs between the quality of solution and runtime, often outperforming the best previously published approaches.
2985827
Flexible ASIC: shared masking for multiple media processors
ASIC provides more than an order of magnitude advantage in terms of density, speed, and power requirement per gate. However, economic (cost of masks) and technological (deep micron manufacturability) trends favor FPGA as an implementation platform. In order to combine the advantages of both platforms and alleviate their disadvantages, recently a number of approaches, such as structured ASIC/regular fabrics, have been proposed. Our goal is to introduce an approach that has the same objective, but is orthogonal to those already proposed. The idea is to implement several ASIC designs in such a way that they share the datapath, memory structure, and several bottom layers of interconnect, while each design has only a few unique metal layers. We identified and addressed two main problems in our quest to develop a CAD flow for realization of such designs. They are: (i) the creation of the datapath, and (ii) the identification of common and unique interconnect for each design. Both problems are solved optimally using ILP formulations. We assembled a design flow platform using two new programs and the Trimaran and Shade tools. We quantitatively analyzed the advantages and disadvantages of the approach using the Mediabench benchmark suite.
60553167
Wire-length prediction using statistical techniques
We address the classic wire-length estimation problem and propose a new statistical wire-length estimation approach that captures the probability distribution function of net lengths after placement and before routing. The wire-length prediction model was developed using a combination of parametric and non-parametric statistical techniques. The model predicts not only the length of the net using input parameters extracted from the floorplan of a design, but also probability distributions that a net with given characteristics obtained after placement will have a particular length. The model is validated using both learn-and-test and resubstitution techniques. The model can be used for a variety of purposes, including the generation of a large number of statistically sound and therefore realistic instances of designs. We applied the net models to the probabilistic buffer insertion problem and obtained substantial improvement in net delay after routing.
926253
Power minimization in QoS sensitive systems
The majority of modern multimedia and mobile systems have two common denominators: quality-of-service (QoS) requirements, such as latency and synchronization, and strict energy constraints. However, until now no synthesis techniques have been proposed for the design and efficient use of such systems. We have two main objectives: conceptual and synthesis. The conceptual objective is to develop a generic practical technique for the automatic development of online adaptive algorithms from efficient off-line algorithms using statistical techniques. The synthesis objective is to introduce the first design technique for QoS low-power synthesis. We introduce a system of provably-optimal techniques that minimize energy consumption of stream-oriented applications under two main QoS metrics: latency and synchronization. Specifically, we study how multiple voltages can be used to simultaneously satisfy hardware constraints and minimize power consumption while preserving the requested level of QoS. The purpose of the off-line algorithm is threefold. First, it is used as input to statistical software which is used to identify important and relevant parameters of the processes. Second, the algorithm provides buffer occupancy rate indicators. Lastly, it provides a way to combine buffer occupancy and QoS metrics to form a fast and efficient online algorithm. The effectiveness of the algorithms is demonstrated on a number of standard multimedia benchmarks.
1973000
Gateway placement for latency and energy efficient data aggregation [wireless sensor networks]
We propose the use of multiple gateways to significantly reduce latency and energy consumption in multi-hop wireless sensor networks during data aggregation. We have derived efficient integer linear programming formulations as well as a novel negative selection statistically-tuned heuristics. The heuristics are based on newly developed relaxation based lower bounds that are also used to quantify the effectiveness of the proposed heuristics. Our simulation study indicates that the use of gateways can often reduce latency and energy consumption by several times.
14591533
Leveraging broadband access for true on-demand delivery of Internet videos
We consider in this paper how the increasingly popular broadband access can be leveraged for scalable and cost-effective video service. Although much work has been done for such service, the existing techniques either are not designed for on-demand video delivery, or do not take into account the vastly improved client receiving capability. In this paper, we address this problem and develop three novel video delivery techniques with two ultimate goals: minimizing service latency and maximize data sharing. With the new techniques, a client can be served as soon as server resource becomes available and meanwhile, all its receiving bandwidth can be used for data receiving. In particular, in the proposed dynamic scheduling algorithm, the efficiency of data sharing is further improved by also exploring server bandwidth for early delivery of video segments. This innovation is contradicted to the intuition that each video segment should be delivered as late as possible in order to maximize data sharing. We evaluate the performance of our new techniques using simulation and our study convincingly shows that with the new schemes, zero service latency can indeed be achieved with very minimal system resource.
45147395
Analysis of a Token Ring Protocol for Voice Transmission
Abstract For voice transmissions in a local-area network, it is desirable to have a small coefficient of variation for the interdeparture time of voice packets at the destination. This may be achieved by the proper design of the medium access protocol. A token ring protocol with provision for voice traffic is considered. An analytic model is developed to study the performance of this protocol with respect to voice traffic. Numerical results showing the effect of model parameters on interdeparture time are presented.
29262099
Transaction models for design environments
Abstract Design data bases used in the design of engineering artifacts have characteristics quite different from conventional data bases. While conventional data bases have, at any given time, a single correct value for each of object, design data bases, due to the presence of design alternates or versions, have available several correct versions of design objects. However, during a design process, when several design objects are involved, the different versions of each object chosen for the design has to be controlled such that they are compatible or version consistent. This article formalizes the notion of version consistency and proposes two transaction models for design processes, where the notion of version consistency itself is used as a basis for scheduling design transactions. A mechanism for enforcing version control is also presented.
8229875
A Reputation-based Trust Management in Peer-to-Peer Network Systems
Peer-to-peer networks have gained a lot of attention over the last couple of years, mainly due to the popularity of the free multimedia file-sharing program Napster and a legal battle around it. Being open by nature P2P systems represent an ideal environment for various types of malicious intrusions. The problem of securing hosts on P2P network while keeping the openness of the system has been studied extensively over last couple of years but still remains open. Existing solutions based on reputation management either employ centralized algorithms or rely on peers' cooperation on the network. We describe a fully decentralized approach that allows computing peers' reputation based on the traffic between a node and its peers, independently of these peers willingness to cooperate in calculation of their reputation. 1 INTRODUCTION Peer-to-peer (P2P) network systems are increasingly gaining popularity on the Internet. These networks allow individual hosts (peers) to share and distribute various types of information over the Internet. By their nature, P2P networks are structured in a way that allows an open and unsupervised communication between peers. Therefore, these systems are vulnerable to various types of attacks, among which are denial-of-service attacks (DoS) and distribution of viruses. To protect themselves from malicious intentions, hosts should be able to identify reliable peers for communication. Identifying these peers is a challenging task in highly dynamic network environments like P2P networks. In this paper we suggest a solution to this problem based on the notion of trust. We propose a policy for managing traffic in peer-to-peer network based on peers' reputation. We also describe a model for computing this reputation using the trust score based on the peers' interaction with each other. Unlike most existing reputation-based models, our approach does not employ a centralized storage and only produces reputation scores on demand. The proposed solution is fully distributed and does not require any cooperation from the rest of the network. Our model aims to help users to select the most reliable peers whose past behavior shows willingness to participate in a proper functioning of the P2P system and at the same time to anticipate possible attacks from malicious peers by limiting their access to the victim peer's resources. In this paper we focus on a particular type of P2P systems, called Gnutella, which proved to be one of the most popular P2P systems. Furthermore, unlike other popular P2P applications such as KaZaa, the source …
28524716
Deterministic projection by growing cell structure networks for visualization of high-dimensionality datasets
Recent advances in clinical proteomics data acquisition have led to the generation of datasets of high complexity and dimensionality. We present here a visualization method for high-dimensionality datasets that makes use of neuronal vectors of a trained growing cell structure (GCS) network for the projection of data points onto two dimensions. The use of a GCS network enables the generation of the projection matrix deterministically rather than randomly as in random projection. Three datasets were used to benchmark the performance and to demonstrate the use of this deterministic projection approach in real-life scientific applications. Comparisons are made to an existing self-organizing map projection method and random projection. The results suggest that deterministic projection outperforms existing methods and is suitable for the visualization of datasets of very high dimensionality.