Designing Hybrid Cooperations with a Component Language for Solving Optimisation Problems

Machine-to-machine (M2M) communication plays an important role in various kinds of intelligent networks. In this study, a hybrid cooperation scheme for data collection in hierarchical smart building networks (SBN) is proposed under the framework of M2M communications. The hierarchical network structure means that the data collection process is carried out via multi-layer communications. In the first layer, smart metres organise themselves into clusters and send information to the cluster-heads. Then all cluster-heads forward the received information to the base station automatically in the second layer. In particular, the roles of cluster-head can be acted by either fixed nodes or user terminals in the building, and this endow a hybrid cooperation mode to the data collection process. To construct the network structure and utilise the resources efficiently, the authors first provide some theoretical analysis on the influence of network structure and bandwidth constraints. Then a distributed scheme for joint structure formation and subband allocation is proposed based on coalitional game theory. Furthermore, for the feasibility of this scheme in practical applications, some improvements of the proposed scheme have also been made at last. The advantages of the proposed scheme are verified by simulation results.

Realizing high-accuracy transmission in high-rate data broadcasting networks with heterogeneous users via cooperative communication

We present a framework to design efficient and portable HPF applications which exploit a mixture of task and data parallelism. According to the framework proposed, data parallelism is restricted within HPF modules, and task parallelism is achieved by the concurrent execution of several data-parallel modules cooperating through COLTHPF, a coordination layer implemented on top of PVM. COLTHPF can be used independently of the HPF compilation system exploited, and it allows instances of cooperating HPF tasks to be created either statically or at run-time. We claim that COLTHPF can be exploited by means of a simple skeleton-based coordination language and associated compiler to easily express mixed data and task parallel applications runnable on either multicomputers or cluster of workstations. We used a physics application as a test case of our approach for mixing task and data parallelism, and we present the results of several experiments conducted on a cluster of Linux SMPs.

Most numerical simulations of the tokamak scrapeoff layer use a mapping to flux coordinates and a piecewise equidistributed grid in those coordinates to resolve multiple length scales and anisotropy. We have developed an alternative numerical method using simple cylindrical coordinates with a complex adaptive grid scheme, based on an unstructured grid of triangles which move adaptively, aligning themselves with the magnetic field and concentrating in regions of sharp gradients.

Cloud computing is now an omnipresent paradigm in modern programming. Cloud applications usually consist of several software components deployed on remote virtual machines. Managing such applications is a challenging problem because manual administration is no longer realistic for these complex distributed systems. Thus, autonomic computing is a promising solution for monitoring and updating these applications automatically. This is achieved through the automation of administration functions and the use of control loops called autonomic managers. An autonomic manager observes the environment, detects changes, and reconfigures dynamically the application. Multiple autonomic managers can be deployed in the same system and must make consistent decisions. Using them without coordination may lead to inconsistencies and error-prone situations. In this paper, we present our approach for coordinating stateful autonomic managers, which relies on a simple coordination language, new techniques for asynchronous controller synthesis and Java code generation. We used our approach for coordinating real-world cloud applications.

A lighting-up fluorescent chemoprobe for nanomolar recognition of diabetic ketoacidosis biomarker D-3-hydroxybutyrate: DFT study and its applications in urine and water samples

Practical packet combining for use with cooperative and non-cooperative ARQ schemes in resource-constrained wireless sensor networks

We report on the an initial experiment where we tackle the coordination challenges inherent in the large scale distribution and parallelisation of bioinformatics workflows. We work towards a common coordination language with which workflow management systems can coordinate with the various analysis tools, operating system, other workflow management systems, schedulers, compute infrastructures and so on. The rationale behind such common coordination language follows the basic claims put forward by Gelernter and Carriero of Linda fame: that it is possible to treat coordination as orthogonal to computation and that it is possible to define coordination in a general way such that it applies to every asynchronous part of the system. Concretely, we implemented a simplified workflow description language called parallel recipes or precipes. As a case study we implemented the Broad reference exome sequencing pipeline in precipes. Important is how this workflow’s parallel execution is implemented using the Concurrent Collections (CnC) coordination language model. We use the Intel CnC++ implementation ( https://icnc.github.io/ ) as an execution platform and execute transparently on top of a workstation, cluster or Amazon EC2 nodes. We demonstrate automatic parallelisation, in-node as well as across-node parallelism and predictable linear scaling. precipes is available on github: https://github.com/yvdriess/precipes/ The video of this presentation is available on the BOSC YouTube channel: view video .

The interaction of Rose Bengal with mannitol-1-phosphate dehydrogenase has been investigated. Binding of this aromatic anionic dye causes a quenching of the protein fluorescence and various changes in the spectral properties of the dye. As is the case with other dehydrogenases, the titration of the enzyme with Rose Bengal, monitoring enhancement in the dye fluorescence at 590 nm, or quenching of the protein fluorescence, can be described by a simple binding model: one dye binding site per enzyme subunit with a dissociation constant of ∼2 µM. However, kinetic studies indicate a more complex scheme, since Rose Bengal induces a biphasic time-dependent inhibition of the enzyme. The first phase is over in 1–5 min and is partially reversible, while the second phase is essentially irreversible and continues beyond 1 h. The dyes 8-anilino-1-naphthalene sulfonate and 2-p-toluidinylnaphthalene-6-sulfonate also cause biphasic time-dependent inhibitions of the enzyme. Only mannitol-1-phosphate, and fructose-6-phosphate in the presence of NAD+, show high levels of protection against these inhibitory processes. The different effects of coenzymes and substrates on the dye-induced inhibitions support earlier observations from fluorescence studies (preceding paper). A binding scheme describing the interactions of Rose Bengal with the enzyme that is consistent with the experimental results is presented.

Cooperative communication is a promising strategy to enhance the performance of a communication network as it helps to improve the coverage area and the outage performance. However, such enhancement comes at the expense of increased resource utilization, which is undesirable; more so in the case of opportunistic wireless systems such as cognitive radio networks. In order to balance the performance gains from cooperative communication against the possible over-utilization of resources, we propose and analyze an adaptive-cooperation technique for underlay cognitive radio networks, termed as hybrid-cooperation. Under the proposed cooperation scheme, secondary users in a cognitive radio network cooperate adaptively to enhance the spectral efficiency and the error performance of the network. The bit error rate, the spectral efficiency and the outage performance of the network under the proposed hybrid cooperation scheme with amplify-and-forward relaying are analyzed in this paper, and compared against conventional cooperation technique. Findings of the analytical performance analyses are further validated numerically through selected computer-based Monte-Carlo simulations. The proposed scheme is found to achieve significantly better performance in terms of the spectral efficiency and the bit error rate, compared to the conventional amplify-and-forward cooperation scheme.

VV4RTOS is an activity supported by the European Space Agency aimed at the development and validation of a framework for the verification and validation of spacecraft guidance, navigation, and control (GNC) systems based on embedded optimisation, tailored to handle different layers of abstraction, from guidance and control (G&C) requirements down to hardware level. This is grounded on the parallel design and development of real-time optimisation-based G&C software, allowing to concurrently identify, develop, consolidate, and validate a set of engineering practices and analysis & verification tools to ensure safe code execution of the designed G&C software as test cases but aimed at streamlining general industrial V&V processes. This paper presents: 1) a review of the challenges and the state-of-the-art of formal verification methods applicable to optimization-based software; 2) the implementation for an embedded application and the analysis from a V&V standpoint of a conic optimization solver; 3) the technical approach devised towards and enhanced V&V process; and 4) experimental results up to processor-in-the-loop tests and conclusions. In general, this activity aims to contribute to the widespread usage of convex optimisation-based techniques across the space industry by 1) augmenting the traditional GNC software Design & Development Verification & Validation (DDVV) methodologies to explicitly address iterative embedded optimisation algorithms that are paramount for the success of new and extremely relevant space applications (from powered landing to active debris removal, from actuator allocation to attitude guidance & control) guaranteeing safe, reliable, repeatable, and accurate execution of the SW; and 2) consolidating the necessary tools for the fast prototyping and qualification of G&C software, grounded on strong theoretical foundations for the solution of convex optimisation problems generated by posing, discretization, convexification, and transcription of nonlinear nonconvex optimal control problems to online-solvable optimisation problems. Sound guidelines are provided for the high-to-low level translation of mission requirements and objectives aiming at their interfacing with verifiable embedded solvers tailored for the underlying hardware and exploiting the structure present in the common optimisation/optimal control problems. To fulfil this mandate, two avenues of research and development were followed: the development of a benchmarking framework with optimisation-based G&C and the improvement of the V&V process – two radical advances with respect to traditional GNC DDVV. On the first topic, the new optimisation-based hierarchy was exploited, from high-level requirements and objectives that can be mathematically posed as optimal control problems, themselves organised in different levels of abstraction, complexity, and time-criticality depending on how close to the actuator level they are. The main line of this work is then focused on the core component of optimisation-based G&C – the optimisation solver – starting with a formal analysis of its mathematical properties that allowed to identify meaningful requirements for V&V, and, concurrently, with a thorough, step-by-step, design and implementation for embedding in a space target board. This application-agnostic analysis and development was associated with the DDVV of specific usecases of optimisation-based G&C for common space applications of growing complexity, exploring different challenges in the form of convex problem complexity (up to second-order cone programs), problem size (model predictive control and trajectory optimization), and nonlinearity (both translation and attitude control problems). The novel V&V approach relies on the combination and exploitation of the two main approaches: classical testing of the global on-board software, and local and compositional, formal, math-driven, verification. While the former sees systems as black boxes, feeding it with comprehensive inputs and analysing statistically the outputs, the latter delves deep into the sub-components of the software, effectively seeing it as white boxes whenever mathematically possible. In between the two approaches lies the optimal path to a thorough, dependable, mathematically sound verification and validation process: local, potentially application-agnostic, validation of the building blocks with respect to mathematical specifications leading up to application-specific testing of global complex systems, this time informed by the results of local validation and testing. The deep analysis of the mathematical properties of the optimisation algorithm allows to derive requirements with increasing complexity (e.g., from “the code implements the proper computations”, to higher level mathematical properties such as optimality, convergence, and feasibility). These are related to quantities of interest that can be both verified resorting to e-ACSL specifications and Frama-C in a C-code implementation of the solver, but also observed in online monitors in Simulink or in post-processing during the model/software-in-the-loop testing. Finally, the activity applies the devised V&V process to the benchmark designs, from model-in-the-loop Monte Carlo testing, followed by autocoding and software-in-the-loop equivalence testing in parallel with the Frama-C runtime analysis, and concluded by processor-in-the-loop testing in a Hyperion on-board computer based around a Xilinx Zynq 7000 SoC.

In recent years, the concept of non-orthogonal multiple access (NOMA) has gathered much attention due to its potential to offer high spectral efficiency, present user fairness and grant free access to sixth generation (6G) vehicular networks. This paper proposes a new optimization framework for NOMA-enabled cooperative vehicular network. In particular, we jointly optimize the vehicle paring, channel assignment, and power allocation at source and relaying vehicles. The objective is to maximize the sum rate of the system subject to the power allocation, minimum rate, relay battery lifetime and successive interference cancelation constraints. To solve the joint optimization problem efficiently, we adopt duality theory followed by Karush-Kuhn-Tucker (KKT) conditions, where the dual variables are iteratively computed through sub-gradient method. Two less complex suboptimal schemes are also presented as the benchmark cooperative vehicular schemes. Simulation results compare the performance of the proposed joint optimization scheme compared to the other benchmark cooperative vehicular schemes.

\n High delay-fault coverage requires rather sophisticated clocking\n schemes in test mode, which usually combine launch-on-shift and\n launch-on-capture strategies. These complex clocking schemes make\n low power test planning more difficult as initialization,\n justification and propagation require multiple clock cycles. This\n paper describes a unified method to map the sequential test planning\n problem to a combinational circuit representation. The combinational\n representation is subject to known algorithms for efficient low\n power built-in self-test planning. Experimental results for a set of\n industrial circuits show that even rather complex test clocking\n schemes lead to an efficient low power test plan.\n

Quickly detecting related primitive events for multiple complex events from massive event stream usually faces with a great challenge due to their single pattern characteristic of the existing complex event detection methods. Aiming to solve the problem, a multiple pattern complex event detection scheme based on decomposition and merge sharing is proposed in this article. The achievement of this article lies that we successfully use decomposition and merge sharing technology to realize the high-efficient detection for multiple complex events from massive event streams. Specially, in our scheme, we first use decomposition sharing technology to decompose pattern expressions into multiple subexpressions, which can provide many sharing opportunities for subexpressions. We then use merge sharing technology to construct a multiple pattern complex events by merging sharing all the same prefix, suffix, or subpattern into one based on the above decomposition results. As a result, our proposed detection method in this article can effectively solve the above problem. The experimental results show that the proposed detection method in this article outperforms some general detection methods in detection model and detection algorithm in multiple pattern complex event detection as a whole.

In this paper, a novel cooperative protocol for free-space optical (FSO) communication systems is proposed, wherein the performance analysis is evaluated over gamma-gamma (GG) fading channels with pointing errors. This novel relaying scheme is based on the optical path selection, source-destination (S-D) or source-relay-destination (S-R-D), with a greater value of fading gain or irradiance together with the use of repetition coding (RC), exploiting the potential time-diversity order available in the turbulent channel in order to maintain a high diversity order. A novel closed-form asymptotic bit-error rate (BER) expression is derived for a 3-way cooperative FSO system. A greater diversity gain with one only relay is corroborated by the obtained results if compared with cooperative FSO schemes of similar complexity at the expense of an information rate-reduction (RR).