Communication Efficient Checking of Big Data Operations

We propose fast probabilistic algorithms with low (i.e., sublinear in the input size) communication volume to check the correctness of operations in Big Data processing frameworks and distributed databases. Our checkers cover many of the commonly used operations, including sum, average, median, and minimum aggregation, as well as sorting, union, merge, and zip. An experimental evaluation of our implementation in Thrill (Bingmann et al., 2016) confirms the low overhead and high failure detection rate predicted by theoretical analysis

Dependability Evaluation of Middleware Technology for Large-scale Distributed Caching

Distributed caching systems (e.g., Memcached) are widely used by service providers to satisfy accesses by millions of concurrent clients. Given their large-scale, modern distributed systems rely on a middleware layer to manage caching nodes, to make applications easier to develop, and to apply load balancing and replication strategies. In this work, we performed a dependability evaluation of three popular middleware platforms, namely Twemproxy by Twitter, Mcrouter by Facebook, and Dynomite by Netflix, to assess availability and performance under faults, including failures of Memcached nodes and congestion due to unbalanced workloads and network link bandwidth bottlenecks. We point out the different availability and performance trade-offs achieved by the three platforms, and scenarios in which few faulty components cause cascading failures of the whole distributed system.Comment: 2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE 2020

ATMP: An Adaptive Tolerance-based Mixed-criticality Protocol for Multi-core Systems

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted ncomponent of this work in other works.The challenge of mixed-criticality scheduling is to keep tasks of higher criticality running in case of resource shortages caused by faults. Traditionally, mixedcriticality scheduling has focused on methods to handle faults where tasks overrun their optimistic worst-case execution time (WCET) estimate. In this paper we present the Adaptive Tolerance based Mixed-criticality Protocol (ATMP), which generalises the concept of mixed-criticality scheduling to handle also faults of other nature, like failure of cores in a multi-core system. ATMP is an adaptation method triggered by resource shortage at runtime. The first step of ATMP is to re-partition the task to the available cores and the second step is to optimise the utility at each core using the tolerance-based real-time computing model (TRTCM). The evaluation shows that the utility optimisation of ATMP can achieve a smoother degradation of service compared to just abandoning tasks

SyRA: early system reliability analysis for cross-layer soft errors resilience in memory arrays of microprocessor systems

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Cross-layer reliability is becoming the preferred solution when reliability is a concern in the design of a microprocessor-based system. Nevertheless, deciding how to distribute the error management across the different layers of the system is a very complex task that requires the support of dedicated frameworks for cross-layer reliability analysis. This paper proposes SyRA, a system-level cross-layer early reliability analysis framework for radiation induced soft errors in memory arrays of microprocessor-based systems. The framework exploits a multi-level hybrid Bayesian model to describe the target system and takes advantage of Bayesian inference to estimate different reliability metrics. SyRA implements several mechanisms and features to deal with the complexity of realistic models and implements a complete tool-chain that scales efficiently with the complexity of the system. The simulation time is significantly lower than micro-architecture level or RTL fault-injection experiments with an accuracy high enough to take effective design decisions. To demonstrate the capability of SyRA, we analyzed the reliability of a set of microprocessor-based systems characterized by different microprocessor architectures (i.e., Intel x86, ARM Cortex-A15, ARM Cortex-A9) running both the Linux operating system or bare metal. Each system under analysis executes different software workloads both from benchmark suites and from real applications.Peer ReviewedPostprint (author's final draft

Fault tolerance of MPI applications in exascale systems: The ULFM solution

[Abstract] The growth in the number of computational resources used by high-performance computing (HPC) systems leads to an increase in failure rates. Fault-tolerant techniques will become essential for long-running applications executing in future exascale systems, not only to ensure the completion of their execution in these systems but also to improve their energy consumption. Although the Message Passing Interface (MPI) is the most popular programming model for distributed-memory HPC systems, as of now, it does not provide any fault-tolerant construct for users to handle failures. Thus, the recovery procedure is postponed until the application is aborted and re-spawned. The proposal of the User Level Failure Mitigation (ULFM) interface in the MPI forum provides new opportunities in this field, enabling the implementation of resilient MPI applications, system runtimes, and programming language constructs able to detect and react to failures without aborting their execution. This paper presents a global overview of the resilience interfaces provided by the ULFM specification, covers archetypal usage patterns and building blocks, and surveys the wide variety of application-driven solutions that have exploited them in recent years. The large and varied number of approaches in the literature proves that ULFM provides the necessary flexibility to implement efficient fault-tolerant MPI applications. All the proposed solutions are based on application-driven recovery mechanisms, which allows reducing the overhead and obtaining the required level of efficiency needed in the future exascale platforms.Ministerio de Economía y Competitividad and FEDER; TIN2016-75845-PXunta de Galicia; ED431C 2017/04National Science Foundation of the United States; NSF-SI2 #1664142Exascale Computing Project; 17-SC-20-SCHoneywell International, Inc.; DE-NA000352

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions