Multiprocessor system-on-chip (MPSoC) has been widely used in many real-time embedded systems where both soft-error reliability (SER) and lifetime (LTR) are key concerns. Many existing works have investigated them, but they focus either on handling one of the two concerns or improving type under constraint other. These techniques thus not applicable to maximize SER LTR simultaneously, which is highly desired some real-world applications. In this paper, we study joint optimization for MPSoCs....

Internet of Things (IoT) devices, such as intelligent road side units and video-based detectors, are being deployed in emerging applications like sustainable transportation systems. The primary obstacles against the development these IoT devices various security threats huge energy consumption. In this article, we study problem scheduling tasks onto a heterogeneous multiprocessor system on chip (MPSoC) for optimizing quality under energy, real-time, task precedence constraints. We first...

CMOS scaling has greatly increased concerns for both lifetime reliability due to permanent faults and soft-error transient faults. Most existing works only focus on one of the two concerns, but often times techniques used increase type may adversely impact other type. A few efforts do consider types together use different metrics quantify reliability. However, many systems, user's concern is maximize system availability by improving mean time failure (MTTF), regardless whether caused or...

The large amount of data produced by satellites and airborne remote sensing instruments has posed important challenges to efficient scalable processing remotely sensed in the context various applications. In this paper, we propose a new big framework for massive amounts images on cloud computing platforms. addition taking advantage parallel abilities cope with large-scale data, incorporates task scheduling strategy further exploit parallelism during distributed stage. Using computation-...

The large data volume and high algorithm complexity of hyperspectral image (HSI) problems have posed big challenges for efficient classification massive HSI repositories. Recently, cloud computing architectures become more relevant to address the computational introduced in field. This article proposes an acceleration method that relies on scheduling metaheuristics automatically optimally distribute workload applications across multiple resources a platform. By analyzing procedure...

Cyber-physical cloud systems (CPCS) are integrations of cyber-physical (CPS) and computing infrastructures. Integrating CPS into infrastructures could improve the performance in many aspects. However, new reliability security challenges also introduced. This fact highlights need to develop novel methodologies tackle these CPCS. To this end, article is oriented toward enhancing soft-error real-time workflows on CPCS while satisfying lifetime reliability, security, constraints. In article, we...

This article gives a survey of state-of-the-art methods for processing remotely sensed big data and thoroughly investigates existing parallel implementations on diverse popular high-performance computing platforms. The pros/cons these approaches are discussed in terms capability, scalability, reliability, ease use. Among distributed platforms, cloud is currently the most promising solution to efficient scalable due its advanced capabilities service-oriented computing. We further provide an...

While the memory footprints of cloud and HPC applications continue to increase, fundamental issues with DRAM scaling are likely prevent traditional main systems, composed monolithic DRAM, from greatly growing in capacity. Hybrid systems can mitigate limitations by pairing together multiple technologies (e.g., different types or non-volatile memory) at same level hierarchy. The goal a hybrid is combine advantages cost-effective manner while avoiding disadvantages each technology. Memory pages...

Heterogeneous multiprocessor system-on-chips (MPSoCs) are suitable platforms for real-time embedded applications that require powerful parallel processing capability as well low power consumption. For such applications, soft-error reliability (SER) due to transient faults and lifetime (LTR) permanent both key concerns. There have been several efforts in the literature oriented toward related problems. However, most existing techniques only concentrate on improving one of two metrics, which...

In cloud-edge computing paradigms, the integration of edge servers and task offloading mechanisms has posed new challenges to developing scheduling strategies. This paper proposes an efficient convergent firefly algorithm (ECFA) for security-critical tasks onto cloud datacenter. The proposed ECFA uses a probability-based mapping operator convert individual into solution, in order associate space with solution space. Distinct from standard FA, employs low-complexity position update strategy...

As the volume of remotely sensed data grows significantly, content-based image retrieval (CBIR) becomes increasingly important, especially for cloud computing platforms that facilitate processing and storing big in a parallel distributed way. This paper proposes novel CBIR system hyperspectral (HSI) repository on under guide unmixed spectral information, i.e., endmembers their associated fractional abundances, to retrieve scenes. However, existing unmixing methods would suffer extremely high...

When designing task scheduling algorithms in mobile edge computing (MEC), the device (MD)'s mobility becomes an important concern, since change MD's location would affect data transmission rate, leading to fluctuations duration and completion time. In this article, we study a mobility-aware off-and-downloading problem MEC, considering both communication delay energy consumption caused by offloading result downloading. We first formulate mathematical optimization model of studied prove its...

Cloud computing has become a promising solution to efficient processing of remotely sensed big data, due its high-performance and scalable capabilities. However, existing cloud solutions generally involve the problems low resource utilization high energy consumption when large-scale remote sensing datasets, affecting quality-of-service system. Aiming at hyperspectral image classification applications, this article proposes an energy-efficient implementation by employing multiobjective task...

With continuously shrinking technology, reliability issues such as Negative Bias Temperature Instability (NBTI) has resulted in considerable degradation of device performance, and eventually the short mean-time-to-failure (MTTF) whole multicore system. This article proposes a new workload balancing scheme based on device-level fractional NBTI model to balance among active cores while relaxing stressed ones. Starting with NBTI-induced threshold voltage degradation, we define concept Capacity...

Cloud storage services give users a great facility in data management such as collection, and sharing, but also bring some potential security hazards. An utmost importance is how to ensure the integrity of files stored cloud, particular for user groups without trusted managers. Existing literature focuses on checking with managers who have lots permissions. To overcome shortage public auditing non-manager clouds, we develop novel framework IPANM that integrates <inline-formula><tex-math...

Mobile crowdsourcing is a new computing paradigm that enables outsourcing computation tasks to mobile crowd nodes by means of offloading the from user edge (MEC) server. This article studies problem scheduling security-critical applications in multiserver MEC environment. We formulate this as an integer program and propose family convergent grey wolf optimizer (CGWO) metaheuristic algorithms seek for best solutions. Our proposed CGWO uses task permutation represent candidate solution...