23906830
PEAS: a robust energy conserving protocol for long-lived sensor networks
Small, inexpensive sensors with limited memory, computing power and short battery lifetimes are turning into reality. Due to adverse conditions such as high noise levels, extreme humidity or temperatures, or even destructions from unfriendly entities, sensor node failures may become norms rather than exceptions in real environments. To be practical, sensor networks must last for much longer times than that of individual nodes, and have yet to be robust against potentially frequent node failures. This paper presents the design of PEAS, a simple protocol that can build a long-lived sensor network and maintain robust operations using large quantities of economical, short-lived sensor nodes. PEAS extends system functioning time by keeping only a necessary set of sensors working and putting the rest into sleep mode. Sleeping ones wake up now and then, probing the local environment and replacing failed ones. The sleeping periods are self-adjusted dynamically, so as to keep the sensors' wakeup rate roughly constant, thus adapting to high node densities.
18977617
Design and analysis of an algorithm for fair service in error‐prone wireless channels
In order to support diverse communication‐intensive real‐time and non‐real‐time data flows over a scarce, varying and shared wireless channel with location‐dependent and bursty errors, we define a service model that has the following characteristics: short‐term fairness among flows which perceive a clean channel, long‐term fairness for flows with bounded channel error, worst‐case delay bounds for packets, short‐term throughput bounds for flows with clean channels and long‐term throughput bounds for all flows with bounded channel error, expanded schedulable region, and support for both delay sensitive and error sensitive data flows. We present the wireless fair service algorithm, and show through both analysis and simulation that it achieves the requirements of the service model in typical wireless network environments. The key aspects of the algorithm are the following: (a) an enhanced fair queueing based service scheme that supports decoupling of delay and bandwidth, (b) graceful service compensation for lagging flows and graceful service degradation for leading flows, (c) support for real‐time delay sensitive flows as well as non‐real‐time error sensitive flows, and (d) an implementation within the framework of the simple and robust CSMA/CA wireless medium access protocol.
1236934
A Packet Scheduling Approach to QoS Support in Multihop Wireless Networks
Providing packet-level quality of service (QoS) is critical to support both rate-sensitive and delay-sensitive applications in bandwidth-constrained, shared-channel, multihop wireless networks. Packet scheduling has been a very popular paradigm to ensure minimum throughput and bounded delay access for packet flows. This work describes a packet scheduling approach to QoS provisioning in multihop wireless networks. Besides minimum throughput and delay bounds for each flow, our scheduling disciplines seek to achieve fair and maximum allocation of the shared wireless channel bandwidth. However, these two criteria can potentially be in conflict in a generic-topology multihop wireless network where a single logical channel is shared among multiple contending flows and spatial reuse of the channel bandwidth is possible. In this paper, we propose a new scheduling model that addresses this conflict. The main results of this paper are the following: (a) a two-tier service model that provides a minimum “fair” allocation of the channel bandwidth for each packet flow and additionally maximizes spatial reuse of bandwidth, (b) an ideal centralized packet scheduling algorithm that realizes the above service model, and (c) a practical distributed backoff-based channel contention mechanism that approximates the ideal service within the framework of the CSMA/CA protocol.
527997
Statistical en-route filtering of injected false data in sensor networks
In a large-scale sensor network individual sensors are subject to security compromises. A compromised node can inject into the network large quantities of bogus sensing reports which, if undetected, would be forwarded to the data collection point (i.e. the sink). Such attacks by compromised sensors can cause not only false alarms but also the depletion of the finite amount of energy in a battery powered network. We present a statistical en-route filtering (SEF) mechanism that can detect and drop such false reports. SEF requires that each sensing report be validated by multiple keyed message authentication codes (MACs), each generated by a node that detects the same event. As the report is forwarded, each node along the way verifies the correctness of the MACs probabilistically and drops those with invalid MACs at earliest points. The sink further filters out remaining false reports that escape the en-route filtering. SEF exploits the network scale to determine the truthfulness of each report through collective decision-making by multiple detecting nodes and collective false-report-detection by multiple forwarding nodes. Our analysis and simulations show that, with an overhead of 14 bytes per report, SEF is able to drop 80/spl sim/90% injected false reports by a compromised node within 10 forwarding hops, and reduce energy consumption by 50% or more in many cases.
11410811
Fair scheduling in wireless packet networks
Fair scheduling of delay and rate-sensitive packet flows over a wireless channel is not addressed effectively by most contemporary wireline fair-scheduling algorithms because of two unique characteristics of wireless media: (1) bursty channel errors and (2) location-dependent channel capacity and errors. Besides, in packet cellular networks, the base station typically performs the task of packet scheduling for both downlink and uplink flows in a cell; however, a base station has only a limited knowledge of the arrival processes of uplink flows. We propose a new model for wireless fair-scheduling based on an adaptation of fluid fair queueing (FFQ) to handle location-dependent error bursts. We describe an ideal wireless fair-scheduling algorithm which provides a packetized implementation of the fluid mode, while assuming full knowledge of the current channel conditions. For this algorithm, we derive the worst-case throughput and delay bounds. Finally, we describe a practical wireless scheduling algorithm which approximates the ideal algorithm. Through simulations, we show that the algorithm achieves the desirable properties identified in the wireless FFQ model.
13148267
Fair scheduling in wireless packet networks
Fair scheduling of delay and rate-sensitive packet flows over a wireless channel is not addressed effectively by most contemporary wireline fair scheduling algorithms because of two unique characteristics of wireless media: (a) bursty channel errors, and (b) location-dependent channel capacity and errors. Besides, in packet cellular networks, the base station typically performs the task of packet scheduling for both downlink and uplink flows in a cell; however a base station has only a limited knowledge of the arrival processes of uplink flows.In this paper, we propose a new model for wireless fair scheduling based on an adaptation of fluid fair queueing to handle location-dependent error bursts. We describe an ideal wireless fair scheduling algorithm which provides a packetized implementation of the fluid model while assuming full knowledge of the current channel conditions. For this algorithm, we derive the worst-case throughput and delay bounds. Finally, we describe a practical wireless scheduling algorithm which approximates the ideal algorithm. Through simulations, we show that the algorithm achieves the desirable properties identified in the wireless fluid fair queueing model.
30892527
On Design and Implementation of Adaptive Data Classification Scheme for DSM Systems
Distributed Shared Memory (DSM) environment is built by using specific softwares, to combine a number of computer hardware resources into one computing environment. Such environment not only provides an easy way to execute parallel applications, but also combines resources to speedup execution of these applications. DSM systems need to maintain data consistency in memory, what usually leads to communication overhead. Therefore, there exist a number of strategies that can be used to overcome this overhead and improve overall performance. Prefetching strategies have been proven to show great performance in DSM systems, since they can reduce data access communication latencies from remote nodes. However, these strategies also transfer unnecessary prefetching pages to remote nodes. In this research paper, we focus on the analysis of data access pattern during execution of parallel applications. We propose an Adaptive Data Classification scheme to improve prefetching strategy, with the goal to improve overall performance. Adaptive Data Classification scheme classifies data according to the access behavior of pages, so that home node uses past history access patterns of remote nodes to decide whether it needs to transfer related pages to remote nodes. From experimental results, our method can improve the performance of prefetching strategies in DSM systems.
1093389
TOPS: An intelligent associate for Turning Operation Planning
This article describes the development of a new modeling environment that supports the building of intelligent associates for turning operation planning. By intelligent associates, we mean a computer-based system that allows a process planner to assert a greater degree of control during a consultation than do traditional expert systems. Intelligent associates are able to assist process planners in a colleague-like manner while solving domain tasks. They relieve routine operations while supporting creative problem-solving. Multiple levels of human experience are supported, advising and constraining inexperienced planners while providing a flexible environment for experienced planners working on new planning strategies. Several Al-based techniques have been employed in the development of this new modeling environment. The utility of this environment is demonstrated by developing a turning operation planning intelligent associate (TOPS). TOPS assists a process planner by computing interactions and checking f...
896953
Sequential Aggregate Signatures and Multisignatures Without Random Oracles
We present the first aggregate signature, the first multisignature, and the first verifiably encrypted signature provably secure without random oracles. Our constructions derive from a novel application of a recent signature scheme due to Waters. Signatures in our aggregate signature scheme are sequentially constructed, but knowledge of the order in which messages were signed is not necessary for verification. The aggregate signatures obtained are shorter than Lysyanskaya et al. sequential aggregates and can be verified more efficiently than Boneh et al. aggregates. We also consider applications to secure routing and proxy signatures.
11276211
PDC: Pattern discovery with confidence in DNA sequences
Pattern discovery in DNA sequences is one of the most challenging tasks in molecular biology and computer science. The main goal of pattern discovery in DNA sequences is to identify sequences of important biological function hidden in the huge amounts of genomic sequences. Several methods and techniques have been proposed and implemented in this field. However, in order to reduce computational time and complexity, most of them either focus on finding short DNA patterns or require explicit specification of pattern lengths in advance. Scientists need to find longer patterns without specifying pattern lengths in advance and still have good performance.In this paper, we propose a pattern discovery algorithm called Pattern Discovery with Confidence (PDC). Based on biological studies, we propose a new measurement system that can identify overrepresented patterns inside DNA sequences. Using this measurement, PDC algorithm can narrow the search space by checking dependency along the pattern, thus extending the pattern as long as possible without the need to restrict or specify the length of a pattern in advance. Experimental tests demonstrate that this approach can find long, interesting patterns within a reasonable computation time.
1764244
Machine Learning in Engineering Automation
Abstract Engineers need intelligent tools to assist them with problems such as design, planning, monitoring, control, diagnosis, and analysis. Manual construction of these tools can be costly or impossible due to problems such as large amounts of data, lack of problem understanding, and the expense of knowledge engineering. Machine learning techniques hold promise for assisting in solutions to many of these problems, but engineering domains present significant challenges to learning systems, including: noisy data, continuous quantities, mathematical formulas, large problem spaces, incorporating multiple sources and forms of knowledge, and the need for user-system interaction. This paper describes a number of challenges to learning systems motivated by engineering applications and describes a taxonomy of engineering tasks for application of machine learning technology.