Low power fault tolerance scheduling scheme in DVS-enabled real-time systems

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.

The use of power monitoring and management system in power enterprises has significantly improved the convenience, fault tolerance, and related economic income of power grid in power supply. At present, there are still many problems in the management system, such as the lack of unified planning. Many functions related to power monitoring and management often need a lot of software to be repeatedly installed in the system to complete the functions required by customers. Meanwhile, this software often has duplicate functions. Power data cannot be shared, and the upgrade of the system will encounter many obstacles. To meet the data communication requirements of component-based power monitoring and management system, this paper applies the characteristics of multi-point distribution and real-time and efficient transmission of data based on model-based information transmission. It also applies component-based data monitoring technology to complete the design. For the power data content of monitoring and calculation, a reusable framework is applied to facilitate user expansion. Users can complete the interface layout by dragging controls on the control interface of the power monitoring and management system, and then realize data customization and saving by binding the database. Finally, the monitoring of the power grid data platforms under cloud service is realized, which is conducive to the effective and timely processing of blowout power grid data. It is of great significance to the safe and stable operation of the power system.

As one of the key characteristics of virtualization, live virtual machine (VM) migration provides great benefits for load balancing, power management, fault tolerance and other system maintenance issues in modern clusters and data centers. Although Pre-Copy is a widespread used migration algorithm, it does transfer a lot of duplicated memory image data from source to destination, which results in longer migration time and downtime. This paper proposes a novel VM migration approach, named Migration with Data Deduplication (MDD), which introduces data deduplication into migration. MDD utilizes the self-similarity of run-time memory image, uses hash based fingerprints to find identical and similar memory pages, and employs Run Length Encode (RLE) to eliminate redundant memory data during migration. Experiment demonstrates that compared with Xen's default Pre-Copy migration algorithm, MDD can reduce 56.60% of total data transferred during migration, 34.93% of total migration time, and 26.16% of downtime on average.

The flexibility offered by mobile agents is quite noticeable in distributed computing environments. However, the greater flexibility of the mobile agent paradigm compared to the client/server computing paradigm comes at an additional threats since agent systems are prone to failures originating from bad communication, security attacks, agent server crashes, system resources unavailability, network congestion, or even deadlock situations. In such events, mobile agents either get lost or damaged (partially or totally) during execution. In this paper, we propose parallel checkpointing approach based on the use of antecedence graphs for providing fault tolerance in mobile agent systems. During normal computation message transmission, the dependency information among mobile agents is recorded in the form of antecedence graphs by participating mobile agents of mobile agent group. When a checkpointing procedure begins, the initiator concurrently informs relevant mobile agents, which minimizes the identifying time. The proposed scheme utilizes the checkpointed information for fault tolerance which is stored in form of antecedence graphs. In case of failures, using checkpointed information, the antecedence graphs and message logs are regenerated for recovery and then normal operation continued. Moreover, compared with the existing schemes, our algorithm involves the minimum number of mobile agents during the identifying and checkpoiting procedure, which leads to the improvement of the system performance. In addition, the proposed algorithm is a domino-free checkpointing algorithm, which is especially desirable for mobile agent systems. Quantitative analysis and experimental simulation show that our algorithm outperforms other coordinated checkpointing schemes in terms of the identifying time and the number of blocked mobile agents and then can provide a better system performance. The main contribution of the proposed checkpointing scheme is the enhancement of graph-based approach in terms of considerable improvement by reducing message overhead, execution, and recovery times.

Energy consumption is one of the most critical constraints in the current VLSI system designs. In addition, fault tolerance of VLSI systems is also one of the most important requirements in the current shrunk VLSI technologies. This paper presents low power and fault tolerant bus encoding methods considering coupling effects of bus interconnects. Experiments using SPEC2000 benchmark programs show that the proposed methods can effectively reduce signal transitions with fault tolerance. Moreover, the results show that the optimization of bus interconnects pitch can increase the effectiveness of the encoding method

Efficient use of electric energy by users is one of the critical ways for increasing energy efficiency, reducing cost of power generation and supply, and environmental concerns. As part of remedial measures to address issues of energy use, many technologies for demand reduction ranging from energy saving devices through a variety of energy management systems have emerged to help users manage and control their consumption. In this paper, we present the design and implementation of a home energy and power management system that enables users to monitor, regulate, and manage their demand response dynamically through scheduling and controlling of their appliances using a mobile application. At the crux of the power management system is an embedded microcontroller which is encoded with schemes for monitoring, managing, scheduling and controlling operations. The user interface on the mobile device directly communicates with the power management system via integrated Raspberry Pi server that uses Wi-Fi communication protocol while communication between the Raspberry Pi and the embedded microcontroller is based on Bluetooth communication. A numerical simulation of the proposed design was first developed and a prototype of the design was implemented and tested. The test results show that the system was able to effectively monitor, control and regulate the power usage in the home. The flexibility offered by the system allows the user to self-regulate the amount of power usage, which translates into cost savings with the overall effect of flattening of the demand peaks.

Power management in advanced power distribution systems integrated with Photovoltaic (PV) sources, batteries, and Super Capacitors (SCs) plays a vital role in ensuring stable and efficient energy flow. However, these systems often face drawbacks such as increased energy consumption due to inefficient control strategies, higher emissions from backup conventional sources during low PV output, and elevated operational costs from frequent battery cycling and system maintenance, despite efforts to improve efficiency and enhance renewable energy utilization. To overcome these drawbacks, this manuscript proposes an approach for optimal power management in a power distribution system with RES. The suggested method is the combination of both the Greater Cane Rat Algorithm (GrCRA) and Pre-Activated Convolution Residual and Triple Attention Mechanism Network (PCRTAM-Net), termed as the GrCRA-PCRTAM-Net approach. The primary aim of the suggested method is to reduce energy consumption, emissions, and operational cost while maximizing efficiency and renewable energy utilization in an advanced power distribution system. GrCRA optimizes the allocation and scheduling of power resources in advanced power distribution systems. PCRTAM-Net predicts future power demand and renewable energy generation patterns to support optimal power management. Flow Direction Algorithm-Convolutional Neural Network (FDA-CNN), Hippopotamus Optimization Algorithm (HOA), Particle Swarm Optimization (PSO), Spider Wasp Optimizer, and Multi-scale Hypergraph-based Feature Alignment Network (SWO-MHFAN), Golden Jackal Optimization-Progressive Conditional Generative Adversarial Network (GJO-PCGAN) are some of the existing techniques that are compared with the suggested method once it is implemented in MATLAB. An 18.7% overall energy reduction compared to the current methods has been achieved by GrCRA-PCRTAM-Net, which also attained an operational cost of 1505 cents, an emission level of 60.3 ppm, an efficiency of 99.1%, and a reduction in overall energy consumption. This further validates that the hybrid method effectively performed power flow optimization and stability enhancement in power distribution networks with renewable integration.

Most of the applications require hard real time signal/data processing potentiality for which fast and dedicated VLSI architectures are the best solution. But designing such circuits lead to high occurrences of failure in the system. Hence there is a critical need for fault tolerance techniques for VLSI designs to increase the reliability of the system. Redundancy techniques are implemented widely to increase the reliability. By developing a fault tolerant system such as Triple Modular Redundancy (TMR), the FPGA can locate the errors and reconfigure the corrupted areas while maintaining the validity of system outputs. One of the drawbacks of this scheme is that the reliability of voter circuit is assumed to be perfect which may not be true. Hence, a novel fault-tolerant voter circuit (NFTVC) have been developed which is more reliable and leads to low power fault tolerant designs. Experimental results show that NFTVC is more reliable than the traditional TMR schemes. The hardware part of the design was done using Spartan-3 kit that is used for a rapid digital circuit. The system performance has been optimized using the Plan Ahead tool in Xilinx in order to reach and maintain the goals of the design. The implementation results provide a simultaneous improvement in power, delay and area.

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

A mobile agent is a software program which migrates from a site to another site to perform tasks assigned by a user. For the mobile agent system to support agents in various application areas, the issues regarding reliable agent execution, as well as compatibility between two different agent systems or secure agent migration, have been considered. Some of the proposed schemes are either replicating the agents (Hamidi & Mohammadi, 2005) or check-pointing the agents (Park, Byun, Kim, & Yeom, 2002; Pleisch & Schiper, 2001;) For a single agent environment without considering inter-agent communication, the performance of the replication scheme and the check-pointing scheme is compared in Park et al. (2002) and Silva, Batista, and Silva (2000). In the area of mobile agents, only few works can be found relating to fault tolerance. Most of them refer to special agent systems or cover only some special aspects relating to mobile agents, such as the communication subsystem. Nevertheless, most people working with mobile agents consider fault tolerance to be an important issue (Izatt, Chan, & Brecht, 1999; Shiraishi, Enokido, & Takzawa, 2003). Mobile agents are becoming a major trend for designing distributed systems and applications in the last few years and foreseeable future. It can bring benefits such as reduced network load and overcoming of network latency (Chan, Won, & Lyu, 1993). Nevertheless, security is one of the limiting factors of the development of these systems. The main unsolved security problem lies in the possible existence of malicious hosts that can manipulate the execution and data of agents (Defago, Schiper, & Sergent, 1998). Most distributed applications we see today are deploying the client/server paradigm. There are certain problems with the client/server paradigm, such as the requirement of a high network bandwidth, and continuous user-computer interactivity. In view of the deficiencies of the client/server paradigm, the mobile code paradigm has been developed as an alternative approach for distributed application design. In the client/server paradigm, programs cannot move across different machines and must run on the machines they reside on. The mobile code paradigm, on the other hand, allows programs to be transferred among and executed on different computers. By allowing code to move between hosts, programs can interact on the same computer instead of over the network. Therefore, communication cost can be reduced. Besides, mobile agent (Fischer, Lynch, & Paterson, 1983) programs can be designed to work on behalf of users autonomously. This autonomy allows users to delegate their tasks to the mobile agents, and not to stay continuously in front of the computer terminal. The promises of the mobile code paradigm bring about active research in its realization. Most researchers, however, agree that security concerns are a hurdle (Greenberg, Byington, & Harper, 1998). In this article, we investigate these concerns. First, we review some of the foundation materials of the mobile code paradigm. We elaborate Ghezzi and Vigna’s classification of mobile code paradigms (Ghezzi & Vigna, 1997), which is a collection of the remote evaluation, code on demand, and mobile agent approaches. In the next section, we address the current status of mobile code security. The following section presents the model for fault-tolerant mobile agent. In the next section, security issues of the mobile agent are discussed, and we discuss security modeling and evaluation for the mobile agent in the section after. In the following section, simulation results and influence of the size of agent are discussed. We then conclude the article.

Fault tolerance engineering has been advocated as one of the main approaches to ensuring the overall system dependability. The 2nd International Workshop on Engineering Fault Tolerant Systems (EFTS 2007) aims to investigate how fault tolerance mechanisms can be taken into account when engineering complex software systems and to improve our understanding of where and how fault-tolerance should be integrated in the software life-cycle. The focus of the workshop is on developing novel models to be applied at different abstraction levels (requirements, architecture and design models for fault tolerance, together with new implementation schemes), innovative technologies (tools and frameworks for implementing distributed fault tolerant systems) and advanced verification environments (to assess the achieved level of fault tolerance and to evaluate the dependability properties of the systems). Recently there has been a growing interest in the areas directly related and overlapping with fault tolerance, such as self-healing, resilience, self-adaptation and self-management. The topics related to engineering of systems with such properties are in the scope of the workshop as the intention is to improve the current understanding of how fault tolerance engineering can benefit from research on these areas.

Modern industry demands techniques that ensure the operability of its processes, and even though the exponential technological advance in the last two decades in the manufacturing field, failures, waste, and unexpected interruptions are still present in this sector's daily routine. Within the Industry 4.0 context, fault-tolerant (FT) production systems remain a complex issue and sometimes represent a vulnerable aspect. Fault-tolerance techniques dedicated to autonomous and distributed systems, in a cyber-physical system (CPS) perspective, need to be investigated to follow the evolutionary pace of the manufacturing scenarios. This paper overviews these concepts and analyses the current situation in developing FT for CPS systems through a systematic literature review. The paper also discusses the research challenges in this new kind of FT systems due to new distributed architectures and emerging technologies, matching the several fault- tolerance phases.

The aim of the article is to systematize the principles for the design and implementation of fault-tolerant information systems amid the rising complexity of distributed, cloud, and cyber-physical architectures and the impossibility of completely eliminating faults; it advances the thesis that service resilience arises as an emergent property through the coordinated application of redundancy, isolation, and recovery mechanisms at all levels—from hardware to organizational. Methodologically, the study relies on theoretical-methodological and comparative analysis, a hermeneutic clarification of the concepts “fault,” “error,” and “failure,” as well as conceptual mapping and tabular systematization of strategies and patterns without conducting experimental measurements; in addition, it considers CAP trade-offs, the cost of redundancy, and the requirements of real-time domains. The scientific novelty lies in a coherent classification of four strategic approaches (redundancy, recovery, error masking, proactive methods), their linkage to canonical architectural patterns (active–passive, active–active, circuit breaker, bulkhead), and tracing the evolution of the fault-tolerance concept from monoliths to distributed and microservice systems and further to CPS with an emphasis on safety; it is shown that “fault tolerance” requires breaking the causal chain “error → failure” through early detection, localization, and limitation of the blast radius. The results demonstrate that single measures have limited effect: the best outcomes are achieved through a multi-layered combination of techniques, where the choice of a specific combination is determined by context—the requirements for consistency and latency, the failure profile, the cost of ownership, and regulatory constraints; the roles of active–passive and active–active clusters, bulkheads, and circuit breakers are shown in reducing the cascading of incidents and maintaining service levels. The discussion articulates practical design principles: explicit decomposition into failure domains, automatic failover and recovery, telemetry of degradation causes, implementation of chaos engineering and predictive maintenance; a reference decision map and criteria for selecting architectures to meet NFR requirements (availability, consistency, security, cost) are proposed, culminating in recommendations for building “defense-in-depth” and formalizing target availability metrics. The practical value lies in the possibility of using the proposed classification as a checklist for engineering choices, and the presented tables as reference material for substantiating SLA/SLO and test scenarios; the theoretical value lies in harmonizing fragmented terminology and deriving invariants of resilience for heterogeneous architectures. A limitation of the study is the qualitative nature of the analysis and the dependence of a number of theses on contextual assumptions; directions for further validation are outlined through empirical cases and observability metrics.

An introduction to Occam 2 programming: Bowler, K C, Kenway, R D, Pawley, G S and Roweth, D Chartwell-Bratt, Bromley, UK (1987) £6.95 pp 115

Due to modern technology trends such as decreasing feature sizes and lower voltage levels, fault tolerance (FT) is becoming increasingly important in computing systems. Several schemes have been proposed to enable a user to configure the FT at the application level, thereby enabling the user to trade stronger FT for performance or vice versa. In this paper, we propose supporting instruction-level rather than application-level configurability of FT, since different parts of some applications (e.g., multimedia) can have different reliability requirements. Weak or no FT will be applied to less critical parts, resulting in time and/or resource gains. These gains can be used to apply stronger FT techniques to the more critical parts; hence increasing the overall reliability. The paper shows how some existing FT techniques can be adapted to support instruction-level FT configurability, how a programmer can specify the desired FT level of the instructions, and how the compiler can manage it automatically. A comparison between the existing FT scheme EDDI (which duplicates all instructions) and the proposed approach is performed both at the kernel and at full application levels. The simulation results show that both the performance and the energy consumption are significantly improved (up to 50% at the kernel and up to 16% at full application level), while the fault coverage depends on the application. For the full application (JPEG encoder), our approach is only applied to one kernel in order to avoid increasing the programming effort significantly.