DDF LOW visualized declarative programming for heterogeneous IoT networks on Heliot testbed platform

Failures are normal rather than exceptional in cloud computing environments, high fault tolerance issue is one of the major obstacles for opening up a new era of high serviceability cloud computing as fault tolerance plays a key role in ensuring cloud serviceability. Fault tolerant service is an essential part of Service Level Objectives (SLOs) in clouds. To achieve high level of cloud serviceability and to meet high level of cloud SLOs, a foolproof fault tolerance strategy is needed. In this paper, the definitions of fault, error, and failure in a cloud are given, and the principles for high fault tolerance objectives are systematically analyzed by referring to the fault tolerance theories suitable for large-scale distributed computing environments. Based on the principles and semantics of cloud fault tolerance, a dynamic adaptive fault tolerance strategy DAFT is put forward. It includes: (i) analyzing the mathematical relationship between different failure rates and two different fault tolerance strategies, which are checkpointing fault tolerance strategy and data replication fault tolerance strategy; (ii) building a dynamic adaptive checkpointing fault tolerance model and a dynamic adaptive replication fault tolerance model by combining the two fault tolerance models together to maximize the serviceability and meet the SLOs; and (iii) evaluating the dynamic adaptive fault tolerance strategy under various conditions in large-scale cloud data centers and consider different system centric parameters, such as fault tolerance degree, fault tolerance overhead, response time, etc. Theoretical as well as experimental results conclusively demonstrate that the dynamic adaptive fault tolerance strategy DAFT has high potential as it provides efficient fault tolerance enhancements, significant cloud serviceability improvement, and great SLOs satisfaction. It efficiently and effectively achieves a trade-off for fault tolerance objectives in cloud computing environments.

<div class="section abstract"><div class="htmlview paragraph">As powertrain hybridization technologies are becoming popular, their application for heavy-duty military vehicles is drawing attention. An intelligent design and operation of the energy management system (EMS) is important to ensure that hybrid military vehicles can operate efficiently, simultaneously maximize fuel economy and minimize monetary cost, while successfully completing mission tasks. Furthermore, an integrated EMS framework is vital to ensure a functional vehicle power system (VPS) to survive through critical missions in a highly stochastic environment, when needed. This calls for situational awareness and dynamic system reconfiguration capabilities on-board of the military vehicle. This paper presents a new energy management and control (EMC) framework based on holistic situational awareness (SA) and dynamic reconfiguration of the VPS. Typical results on a notional hybrid ground vehicle power system are presented to illustrate: 1) mission tasks power requirements and respective priority assignments; and 2) roles of situational awareness and dynamic reconfiguration layer in the operation of the proposed integrated energy management and control framework.</div></div>

Fault tolerant aggregation in heterogeneous sensor networks

In this era of ubiquitous computing, coupled with the emergence of big data and internet of things, there have been constant changes in every aspect of cloud data center communications - its network connectivity, data storage, data transfer, and architectural design. As a result of this, the amount of data transferable, and the frequency of data transfer have tremendously increased; causing device failures and traffic congestions. To cope with these changes so that performance can be sustained amidst device failures and traffic congestion, the design of fault tolerant cloud data center is important. A fault tolerant cloud data center network should be able to provide alternative paths from source to destination during failures so that there will not be abrupt fall in performance. But still with the ongoing researches in this regard, there has not been a robust cloud data center design that can boast of being suitable for alleviating the poor fault tolerance of cloud data center. In this paper, we proposed the improved versions of fat-tree interconnection hybrid designs derived from the structure called Z-fat tree; to address the issues of fault tolerance. Then, we compared these designs with single fat tree architecture with the same amount of resources for client server communication pattern such as Email application in a cloud data center. The simulation results obtained based on failed switches and links, show that our proposed hybrid designs outperformed the single fat tree design as the inter arrival time of the packets reduces.

Universal middleware bridge (UMB) provides seamless interoperation among heterogeneous home network middleware. There have been high demands for the UMB components (UMB core and adaptors) to have fault- tolerance capabilities. This paper presents a TMO structuring approach together with new implementation techniques for the fault-tolerant TMO-replica structuring scheme called PSTR. PSTR implementations of UMB components provide fault tolerance capabilities essential in realizing high reliability for the UMB facility.

The author provides an overview of various key features of De Bruijn graph-based VLSI architectures. The advantages of De Bruijn architectures over such other architectures as cube and shuffle-exchange are discussed. Important differences between De Bruijn interconnects and others are also described. The evolution of the De Bruijn interconnect is described. The FFT architecture and the Viterbi decoder for convolutional codes are examined in detail. The issues of routing and fault tolerance are addressed. >

When ASICs are dedicated to highly dependable applications, concurrent checking and/or fault-tolerance capabilities are necessary on chip. In particular, FSMs must be protected against permanent and transient faults. The authors review the main proposals one can fine on this subject in the literature. Then, an approach is proposed to achieve intrinsic fault tolerance. This approach is based on a specific logic synthesis for FSMs described by their state transition graph. >

We report a multispectral imaging microscope with dynamic spectral reconfiguration capability. It operates based on a spatial filtering principle. The objective lens images the test specimen onto a dispersive grating surface. A dynamic spatial filter located at the Fourier plane of the 4-f lens group is used to select the desired spectral channel and spectral width for each spectral image diffracted by the grating. The reconfiguration capability enables the optimal spectral band selection for a specific application without hardware component modification. Successful experimental results validate the microscopic multispectral imaging configuration for practical applications.

Resource virtualization on FPGA devices, achievable due to its dynamic reconfiguration capabilities, provides an attractive solution to save silicon area. Architectural synthesis for dynamically reconfigurable FPGA-based digital systems needs to consider the case of reducing the number of temporal partitions (reconfigurations) by enabling sharing of some functional units in the same temporal partition. This paper proposes a novel algorithm for automated datapath design from behavioral input descriptions (represented by an acyclic dataflow graph), which simultaneously performs temporal partitioning and sharing of functional units. The proposed algorithm attempts to minimize both the number of temporal partitions and the execution latency of the generated solution. Temporal partitioning, resource sharing, scheduling, and a simple form of allocation and binding are all integrated in a single task. The algorithm is based on heuristics and on a new concept of construction by gradually enlarging timing slots. Results show the efficiency and effectiveness of the algorithm when compared to existent approaches.

In this paper, we address the design and management issues in routing a mixture of OC-192 and OC-768 streams in wavelength-routed optical networks. We assume that fiber links in the network are heterogeneous with respect to their transmission capability (i.e., links are designed to handle a given maximum bit-rate imposed by regenerator spacing). We investigate the issues of routing connection demands of various bit-rate requirements in such heterogeneous networks. In this environment, we introduce the routing of multirate traffic (RMT) problem. The RMT problem is informally defined as the process of finding the best routing which maximizes the total bandwidth carried in the network, for a set of sessions, within a given TDM equipment budget. We propose a two-phase optimization scheme (two-phase RMT). This scheme first obtains a basis solution used in routing 40-Gb/s traffic only on OC-768 capable links without the use of TDM equipment. In the second phase, an iterative routing, rerouting, and resource allocation step is used to optimize the total bandwidth carried in the network, while allowing 40-Gb/s traffic to be routed on OC-768 incapable links by the proper installation of TDM multiplexors and demultiplexers at some strategic locations in the network. Numerical results reveal the following: 1) the two-phase RMT optimization algorithm provides substantial savings in terms of both the total TDM equipment installed and number of wavelengths used; 2) noticeable enhancements of the bandwidth utilization and the TDM budget are observed when the route-optimization takes into account the transmission quality of the links; and 3) the use of intermediate TDM multiplexing/demultiplexing functions provides substantial savings, in terms of the total number of channels, over the source-splitting scheme.

We achieved external activation of local hot-spot sites in supracolloidal assembly structures. The concept was demonstrated by boosting surface-enhanced Raman scattering (SERS) efficiency by one order of magnitude through a heating-induced process. Our approach involves assembling gold nanoparticles with distinct dimensions, i.e. 16 and 80 nm, into well-defined planet-satellite-type arrangement structures using thermoresponsive (poly(N-isopropylacrylamide)) star polymer linkers. Insights into the assembly process were obtained by calculations within the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory framework. We observe one order of magnitude increase in SERS enhancement by a heating-induced volume-phase transition. This magnification aligns with simulations run using the finite-difference time-domain (FDTD) method. The implications of this adaptive supracolloidal concept are twofold: Firstly, our approach bypasses limitations of existing systems that are associated with the limited accessibility of electromagnetic hot-spot sites in strongly coupled, static assemblies of plasmonic nanoparticles, by providing the capability of dynamic hot-spot re-configuration. Second, these externally activated probes offer promising opportunities for the development of messenger materials and associated sensing strategies.

Field-Programmable Gate Arrays (FPGAs) provide highly flexible platforms to implement sophisticated data processing for scientific space instruments. The dynamic partial reconfiguration (DPR) capability of FPGAs allows it to schedule HW tasks. While this feature adds another dimension of processing power that can be exploited without significantly increasing system complexity and power consumption, there are still several challenges for an efficient DPR use. State-of-the-art concepts concentrate either on resource-efficient implementations at design time or flexible HW task scheduling at runtime. In this paper we propose a balanced algorithm that considers both optimization goals and is well suited for resource-limited space applications.

A Givens rotation based scalable QRD core which utilizes an efficient pipelined and unfolded 2D multiply and accumulate (MAC) based systolic array architecture with dynamic partial reconfiguration (DPR) capability is proposed. The square root and inverse square root operations in the Givens rotation algorithm are handled using a modified look-up table (LUT) based Newton-Raphson method, thereby reducing the area by 71% and latency by 50% while operating at a frequency 49% higher than the existing boundary cell architectures. The proposed architecture is implemented on Xilinx Virtex-6 FPGA for any real matrices of sizem×n, where4≤n≤8andm≥nby dynamically inserting or removing the partial modules. The evaluation results demonstrate a significant reduction in latency, area, and power as compared to other existing architectures. The functionality of the proposed core is evaluated for a variable length adaptive equalizer.

Most of the widely used renewable energy sources like PV systems produce DC output and in order to integrate this output with AC grid, an efficient inverter system with fault tolerance is essential. Even for a little period of time, a switch defect in an inverter might have a negative impact on the related essential loads. While considering the several advantages and applications, cascaded multilevel inverter(CHB MLI) can significantly improve system reliability through its fault-tolerant operation due to its switching redundancy. Many multilevel inverters with several control strategies are proposed in literature, but only fewer inverters are with fault tolerant capability. This research suggests a hybrid H-bridge-based CHB MLI architecture that is fault-tolerant. The inverter is capable of operating with rated power under multiple switch open fault conditions. A five-level fault tolerant CHB MLI is simulated and analysed under various fault conditions. Reconfiguration of inverter is possible under input source variations is also possible in this system. The operation of inverter is validated with experimental results. This inverter is suitable for industrial drives, battery energy storage systems and uninterrupted power systems where reliable operation is needed.

Numerous researchers have suggested numerous solutions based on routing and energy to overcome the prevalence of WSN faults in the current literature. Clustering is the most commonly used energy-efficient and fault-tolerant management technique in WSNs, grouping sensors to manage them and perform distributed activities such as resource management. Although clustering methods are most commonly used to reduce energy consumption, they can also achieve various quality-driven goals, such as network fault tolerance capability. As a result of WSN's unpredictable nature, developing fault tolerance mechanisms is essential. Redundancy and diversity methods are commonly used in networks to increase fault tolerance. As a network management challenge, clustering methods should tolerate malfunctioning sensors while maintaining the network's coverage and stability. Sensors are prone to failure due to their operation in hostile environments with limited battery power. The state of the deployed sensor or cluster head (CH) can be active, redundant, or dead/faulty for the same target region of interest (R). The network's overall lifetime and fault tolerance capability can also be extended by using these backup sensors. By putting redundant sensors into sleep mode, can extend the network lifetime without compromising the quality of service. Sensor networks are generally designed to endure far longer than individual sensors. It is commonly performed by putting sensors to sleep. We propose a robust distributed clustered fault tolerance scheduling (RDCFT) approach that efficiently checks the status of the deployed sensor periodically (based on a sweep-line redundancy check algorithm) in WSNs. Simulation results are based on analytical and experimental studies to validate the effectiveness and usefulness of the proposed work.