The Experts below are selected from a list of 30003 Experts worldwide ranked by ideXlab platform

Suman Nath - One of the best experts on this subject based on the ideXlab platform.

  • ace exploiting correlation for energy efficient and continuous context sensing
    IEEE Transactions on Mobile Computing, 2013
    Co-Authors: Suman Nath
    Abstract:

    We propose an acquisitional context engine (ACE), a middleware that supports continuous context-aware applications while mitigating sensing costs for inferring contexts. The ACE provides user's current context to applications running on it. In addition, it dynamically learns relationships among various context attributes (e.g., whenever the user is Driving, he is not AtHome). The ACE exploits these automatically learned relationships for two powerful optimizations. The first is inference caching that allows the ACE to opportunistically infer one context attribute (AtHome) from another already-known attribute (Driving), without acquiring any sensor data. The second optimization is speculative sensing that enables the ACE to occasionally infer the value of an expensive attribute (e.g., AtHome) by sensing cheaper attributes (e.g., Driving). Our experiments with two real context traces of 105 people and a Windows Phone prototype show that the ACE can reduce sensing costs of three context-aware applications by about 4.2 times, compared to a raw sensor data cache shared across applications, with a very small memory and Processing Overhead.

  • ace exploiting correlation for energy efficient and continuous context sensing
    International Conference on Mobile Systems Applications and Services, 2012
    Co-Authors: Suman Nath
    Abstract:

    We propose ACE (Acquisitional Context Engine), a middleware that supports continuous context-aware applications while mitigating sensing costs for inferring contexts. ACE provides user's current context to applications running on it. In addition, it dynamically learns relationships among various context attributes (e.g., whenever the user is Driving, he is not AtHome). ACE exploits these automatically learned relationships for two powerful optimizations. The first is inference caching that allows ACE to opportunistically infer one context attribute (AtHome) from another already-known attribute (Driving), without acquiring any sensor data. The second optimization is speculative sensing that enables ACE to occasionally infer the value of an expensive attribute (e.g., AtHome) by sensing cheaper attributes (e.g., Driving). Our experiments with two real context traces of 105 people and a Windows Phone prototype show that ACE can reduce sensing costs of three context-aware applications by about 4.2x, compared to a raw sensor data cache shared across applications, with a very small memory and Processing Overhead.

Nirwan Ansari - One of the best experts on this subject based on the ideXlab platform.

  • accommodating fragmentation in deterministic packet marking for ip traceback
    Global Communications Conference, 2003
    Co-Authors: Andrey Belenky, Nirwan Ansari
    Abstract:

    A modification to the basic deterministic packet marking (DPM), a promising IP traceback scheme, to handle fragmented traffic is proposed. The modification introduces no additional bandwidth Overhead, but limited additional memory requirements and Processing Overhead on the DPM-enabled interface.

  • tracing multiple attackers with deterministic packet marking dpm
    Pacific Rim Conference on Communications Computers and Signal Processing, 2003
    Co-Authors: A Belenky, Nirwan Ansari
    Abstract:

    The rising threat of cyber attacks, especially distributed denial-of-service (DDoS), and makes the IP traceback problem very relevant to today's Internet security. IP traceback is one of the security problems associated with identifying the source of the attack packets. This work presents a novel approach to IP traceback - deterministic packet marking (DPM). The proposed approach is scalable, simple to implement, and introduces no bandwidth and practically no Processing Overhead on the network equipment It is capable of tracing thousands of simultaneous attackers during DDoS attack. All of the Processing is done at the victim. The traceback process can be performed post-mortem, which allows for tracing the attacks that may not have been noticed initially. The involvement of the Internet service providers (ISP) is very limited, and changes to the infrastructure and operation required to deploy DPM are minimal. DPM performs the traceback without revealing the internal topology of the provider's network, which is a desirable quality of a traceback scheme.

  • Accommodating Fragmentation in Deterministic Packet Marking for IP Traceback
    2003
    Co-Authors: Andrey Belenky, Nirwan Ansari
    Abstract:

    We propose a modification to the basic Deterministic Packet Marking (DPM), a promising IP traceback scheme, to handle fragmented traffic. The modification introduces no additional bandwidth Overhead, but limited additional memory requirements and Processing Overhead on the DPM-enabled interface

P Banerjee - One of the best experts on this subject based on the ideXlab platform.

  • a parallel implementation of a fast multipole based 3 d capacitance extraction program on distributed memory multicomputers
    Journal of Parallel and Distributed Computing, 2001
    Co-Authors: Yanhong Yuan, P Banerjee
    Abstract:

    Very fast and accurate 3-D capacitance extraction is essential for interconnect optimization in VLSI ultra-deep sub-micron designs (UDSM). Parallel Processing provides an approach to reducing the simulation turn-around time. This paper examines the parallelization of the well-known fast multipole-based 3-D capacitance extraction program FASTCAP, which employs new adaptive and preconditioning techniques. To account for the complicated data dependencies in the unstructured problems, we propose a novel generalized cost function model, which can be used to accurately measure the workload associated with each cube in the hierarchy. We then present two adaptive partitioning schemes, combined with efficient communication mechanisms with bounded buffer size, to reduce the parallel Processing Overhead. The overall load balance is achieved through balancing the load at each level of the multipole computation. We report detailed performance results on a variety of distributed memory parallel platforms, using standard benchmarks on 3-D capacitance extraction.

  • a parallel implementation of a fast multipole based 3 d capacitance extraction program on distributed memory multicomputers
    International Parallel and Distributed Processing Symposium, 2000
    Co-Authors: Yanhong Yuan, P Banerjee
    Abstract:

    Very fast and accurate 3-D capacitance extraction is essential for interconnect optimization in ultra deep sub-micro designs (UDSM). Parallel Processing provides an approach to reducing the simulation turn-around time. This paper examines the parallelization of the well known fast multipole based 3-D capacitance extraction program FASTCAP, which employs new preconditioning and adaptive techniques. To account for the complicated data dependencies in the unstructured problems, we propose a generalized cost function model, which can be used to accurately measure the workload associated with each cube in the hierarchy. We then present two adaptive partitioning schemes, combined with efficient communication mechanisms with bounded buffer size, to reduce the parallel Processing Overhead. The overall load balance is achieved through balancing the load at each level of the multipole computation. We report detailed performance results using a variety of standard benchmarks on 3-D capacitance extraction, on an IBM SP2.

C S Raghavendra - One of the best experts on this subject based on the ideXlab platform.

  • soft timeout distributed key generation for digital signature based on elliptic curve d log for low power devices
    International Workshop on Security, 2005
    Co-Authors: Caimu Tang, Anthony T Chronopoulos, C S Raghavendra
    Abstract:

    Group based transactions are becoming common via handhelds. Single key based systems may not be able to meet various security requirements. In this paper, we propose a threshold signature scheme based on Pedersen distributed key generation principle which is suitable for handheld devices and ad-hoc networks. Existing distributed key generation protocols use either cryptosystems based on the hardness of discrete logarithm over a finite field or integer factorization. Elliptic curve cryptosystems provide a promising alternative with efficiency which is suitable for low-power devices in terms of memory and Processing Overhead. In the proposed scheme, the public key from the key generation protocol follows a uniform distribution in the elliptic curve additive group, and the signature can be generated and verified efficiently. We evaluated the proposed key generation protocol and signature scheme using PARI/GP, and the key generation time takes a fraction of a second and the signature signing and verifying can be finished in a few milliseconds on the LINUX Intel PXA 255 processor.

Eliot J B Moss - One of the best experts on this subject based on the ideXlab platform.

  • efficient packet demultiplexing for multiple endpoints and large messages
    USENIX Winter Technical Conference, 1994
    Co-Authors: Masanobu Yuhara, Brian N Bershad, Chris Maeda, Eliot J B Moss
    Abstract:

    This paper describes a new packet filter mechanism that efficiently dispatches incoming network packets to one of multiple endpoints, for example address spaces. Earlier packet filter systems iteratively applied each installed filter against every incoming packet, resulting in high Processing Overhead whenever multiple filters existed. Our new packet filter provides an associative match function that enables similar but not identical filters to be combined together into a single filter. The filter mechanism, which we call the Mach Packet Filter (MPF), has been implemented for the Mach 3.0 operating system and is being used to support endpoint-based protocol Processing, whereby each address space implements its own suite of network protocols. With large numbers of registered endpoints, MPF outperforms the earlier BSD Packet Filter (BPF) by over a factor of four. MPF also allows a filter program to dispatch fragmented packets, which was quite difficult with previous filter mechanisms.