Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

The Transmission Control Protocol.

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Design Of Analog Cmos Integrated Circuits

Data centers are critical, energy-hungry infrastructures that run large-scale Internet-based services. Energy consumption models are pivotal in designing and optimizing energy-efficient operations to curb excessive energy consumption in data centers. In this paper, we survey the state-of-the-art techniques used for energy consumption modeling and prediction for data centers and their components. We conduct an in-depth study of the existing literature on data center power modeling, covering more than 200 models. We organize these models in a hierarchical structure with two main branches focusing on hardware-centric and software-centric power models. Under hardware-centric approaches we start from the digital circuit level and move on to describe higher-level energy consumption models at the hardware component level, server level, data center level, and finally systems of systems level. Under the software-centric approaches we investigate power models developed for operating systems, virtual machines and software applications. This systematic approach allows us to identify multiple issues prevalent in power modeling of different levels of data center systems, including: i) few modeling efforts targeted at power consumption of the entire data center ii) many state-of-the-art power models are based on a few CPU or server metrics, and iii) the effectiveness and accuracy of these power models remain open questions. Based on these observations, we conclude the survey by describing key challenges for future research on constructing effective and accurate data center power models.

Data Center Energy Consumption Modeling: A Survey

The Internet of Things (IoT) provides the ability for humans and computers to learn and interact from billions of things that include sensors, actuators, services, and other Internet-connected objects. The realization of IoT systems will enable seamless integration of the cyber world with our physical world and will fundamentally change and empower human interaction with the world. A key technology in the realization of IoT systems is middleware, which is usually described as a software system designed to be the intermediary between IoT devices and applications. In this paper, we first motivate the need for an IoT middleware via an IoT application designed for real-time prediction of blood alcohol content using smartwatch sensor data. This is then followed by a survey on the capabilities of the existing IoT middleware. We further conduct a thorough analysis of the challenges and the enabling technologies in developing an IoT middleware that embraces the heterogeneity of IoT devices and also supports the essential ingredients of composition, adaptability, and security aspects of an IoT system.

IoT Middleware: A Survey on Issues and Enabling Technologies

By using Elliptic Curve Cryptography (ECC), it has been recently shown that Public-Key Cryptography (PKC) is indeed feasible on resource-constrained nodes This feasibility, however, does not necessarily mean attractiveness, as the obtained results are still not satisfactory enough In this paper, we present results on implementing ECC, as well as the related emerging field of Pairing-Based Cryptography (PBC), on two of the most popular sensor nodes By doing that, we show that PKC is not only viable, but in fact attractive for WSNs As far as we know pairing computations presented in this paper are the most efficient results on the MICA2 (8-bit/73828-MHz ATmega128L) and Tmote Sky (16-bit/8192-MHz MSP-430) nodes

/pdf/nanoecc-testing-the-limits-of-elliptic-curve-cryptography-in-1ruhlxqrax.pdf

NanoECC: testing the limits of elliptic curve cryptography in sensor networks

Recent research results have shown that Elliptic Curve Cryptography (ECC) is feasible on resource constrained sensor nodes. In this work we demonstrate that the related but more complex primitives of Pairing Based Cryptography(PBC) are also well suited for sensor devices.We present the first in-depth study on the application and implementation of PBC to Wireless Sensor Networks (WSNs). Our implementations are all the fastest yet reported, and have been implemented across a range of WSN processors. On a system level we investigate the application of a simple non-interactive key exchange scheme that is particularly suitable for many WSN scenarios. We also present a novel variant of the key exchange protocol which can be useful in even more demanding applications, and which partially solves the problem of node compromise attacks.

On the application of pairing based cryptography to wireless sensor networks

The hop distance strategy in wireless sensor networks (WSNs) has a major impact on energy consumption of each sensor mote. Long-hop routing minimizes reception cost. However, a substantial power demand is incurred for long distance transmission. Since the transceiver is the major source of power consumption in the node, optimizing the routing for hop length can extend significantly the lifetime of the network. This paper explores when multi-hop routing is more energy efficient than direct transmission to the sink and the conditions for which the two-hop strategy is optimal. Experimental evidence is provided in to support of these conclusions. The tests showed that the superiority of the multi-hop scheme depends on the source-sink distance and reception cost. They also demonstrated that the two- hop strategy is most energy efficient when the relay is at the midpoint of the total transmission radius. Our results may be used in existing routing protocols to select optimal relays or to determine whether it is better to send packets directly to the base station or through intermediate nodes.

/pdf/on-the-problem-of-energy-efficiency-of-multi-hop-vs-one-hop-2rdq558al3.pdf

On the Problem of Energy Efficiency of Multi-Hop vs One-Hop Routing in Wireless Sensor Networks

In telecommunications networks, distributed power management across heterogeneous hardware requires a standardized representation of each system's capabilities to decouple distributed high-level algorithms from hardware specifics. The Green Abstraction Layer (GAL) provides this interface between high-level algorithms and a lower level representing the hardware and physical resources that directly exert energy management and actions in a network.

The Green Abstraction Layer: A Standard Power-Management Interface for Next-Generation Network Devices

The area of security for Heterogeneous Sensor Networks (HSNs) is still an open research field that requires new cryptographic solutions. Recent results have demonstrated that Elliptic Curve Cryptography (ECC) and Pairing-Based Cryptography (PBC) are computationally feasible on sensor devices. This allows a wide range of novel security mechanisms, like Identity-Based Encryption (IBE), to be considered for Wireless Sensor Networks (WSNs). In this paper we present an efficient security bootstrapping mechanism for HSNs that uses IBE and exploits the enhanced capabilities of high-end cluster heads. Our asymmetric security scheme provides authenticated key distribution without using expensive certificates. It also achieves significant savings in communication overhead and in the number of keys stored on sensor devices. We also present TinyIBE, which is to our knowledge, the first implementation of a complete identity-based encryption scheme for sensor networks. Our evaluation results and comparison with the state of the art show that TinyIBE is a superior security scheme for HSNs which provides affordable public key cryptography without requiring hardware acceleration. With this work we prove that ID-based encryption is not only possible on sensor nodes but is an attractive security solution in this application space.

/pdf/tinyibe-identity-based-encryption-for-heterogeneous-sensor-4c81ftkbt4.pdf

Martin Collier

Papers

NanoECC: testing the limits of elliptic curve cryptography in sensor networks

On the application of pairing based cryptography to wireless sensor networks

On the Problem of Energy Efficiency of Multi-Hop vs One-Hop Routing in Wireless Sensor Networks

The Green Abstraction Layer: A Standard Power-Management Interface for Next-Generation Network Devices

TinyIBE: Identity-based encryption for heterogeneous sensor networks