Mobile Edge Cloud Computing (MECC) has becoming an attractive solution for augmenting the computing and storage capacity of Devices (MDs) by exploiting available resources at network edge. In this work, we consider computation offloading mobile edge cloud that is composed a set Wireless (WDs), each WD energy harvesting equipment to collect renewable from environment. Moreover, multiple MDs intend offload their tasks simultaneously. We first formulate multi-user multi-task problem green MECC,...

In this paper, with the aims of alleviating pressure from shortage spectrum resource and addressing inefficient utilization, we investigate sharing for moving vehicles in Heterogeneous Vehicular Networks (HVNs) consisting macrocells Road Side Units (RSUs) Cognitive Radio (CR) technology. We first propose an incentive mechanism encouraging to share vehicle users, which CR-enabled RSUs perform sensing availability surrounding urban environments. Furthermore, downlink allocation users...

Mobility load balancing (MLB) is widely used to address the uneven distribution problem. The basic idea that a hot-spot cell selects less-loaded neighbouring cells as assistant cells, and thenshiftsitsedge users via handover region adjustment. However, shifted receive reduced signal power after MLB, which may result in poor link quality problem for users. In order deal with this problem, paper proposes mobility aware radio resource allocation (MLBRRA) scheme. MLBRRA scheme, jointly considers...

Simultaneous wireless information and power transfer (SWIPT) transmits powers nodes with the same radio frequency signal. It can prolong life time of energy-constrained nodes. Current works SWIPT focus on one-hop two-hop network. In order to verify performance in multi-hop network (MECWN) where energy harvested by receiver node be as an compensation for data forwarding, this paper concurrently considers routing selection MECWN. To reduce consumption, we first formulate allocation problem...

Task clustering has proven to be an effective method reduce execution overhead and improve the computational granularity of scientific workflow tasks executing on distributed resources. However, a job composed multiple may have higher risk suffering from failures than single task job. In this paper, we conduct theoretical analysis impact transient runtime performance executions. We propose general failure modeling framework that uses maximum likelihood estimation-based parameter estimation...

Time synchronization is a fundamental requirement for wireless communication systems to work properly. Most of the existing studies focus on time among homogeneous devices. This investigates with heterogeneous technologies (e.g., WiFi, ZigBee, and Bluetooth) which important rising Internet Thing (IoT) scenarios where devices coexist. Recent advances in cross-technology (CTC) break wall between In this work, we propose new strategy based CTC technique provide called TimeBee, takes advantage...

Wireless localization, especially using ubiquitous Wi-Fi devices, has been studied for decades. However, due to complex signal propagation, resolving multiple reflected paths and further achieving accurate localization face great challenges in the precision range, which are caused by limited bandwidth sensitivity of signals respectively. Straightforwardly solving these employing wide is only helpful improving precision, while range still short Wi-Fi's intrinsic vulnerability SNR drop. This...

Scientific workflows can be composed of many fine computational granularity tasks. The runtime these tasks may shorter than the duration system overheads, for example, when using multiple resources a cloud infrastructure. Task clustering is optimization technique that merges short into single job such scheduling overhead reduced and overall performance improved. However, existing task strategies only provide coarse-grained approach relies on an over-simplified workflow model. In our work, we...

Electric utilities have been investigating methods to reduce peak power demand. Demand response (DR) is one such method which intends electricity DR programs typically limits on the number and timing of events that may be triggered for a selected group customers. This paper presents methodology optimizing scheduling various programs. The proposed optimization mechanism establishes policy triggers according criteria govern cost utility based probability distributions exogenous information...

The recent increased use of workflow management systems by large scientific collaborations presents the challenge scheduling large-scale workflows onto distributed resources. This work aims to partition in conjunction with resources provisioning reduce make span and resource cost.

The execution of scientific workflows often suffers from a variety overheads in distributed environments. It is essential to identify the different and evaluate how optimization methods help reduce improve runtime performance. In this paper, we present an overhead analysis for set workflow runs on cloud grid platforms. We distributions conclude that they satisfy exponential or uniform distribution. compare three calculate cumulative sum based overlap. addition, indicate experimental...

Deduplication has become a widely deployed technology in cloud data centers to improve IT resources efficiency. However, traditional techniques face great challenge big deduplication strike sensible tradeoff between the conflicting goals of scalable throughput and high duplicate elimination ratio. We propose AppDedupe, an application-aware inline distributed framework environment, meet this by exploiting application awareness, similarity locality optimize with inter-node two-tiered routing...

Network Anomaly Detection plays an important part in network security. Among the state-of-the-art approaches, unsupervised anomaly detection is effective when dealing with unlabelled data. However, these approaches also suffer from high false positive rate. We observed that different methods have their own defects and advantages. Inspired by this observation, we provide a new ensemble clustering(NEC) method to detect novel anomalies. In our system, can get higher rate lower compared existed...

Short-term traffic flow prediction plays a crucial component in transportation management and deployment. In this paper, novel regression framework for short-term with automatic parameter tuning is proposed, the SVR being primary model Bayesian Optimization major method parameters selection. First, preprocessing of raw carried out by seasonal difference to eliminate non-stationary data. Then, Support Vector Regression trained pre-processed order optimize parameters, generalization...

Traditional analysis of the wireless network operation stability (WNOS) is based on several indicators or human experience, there a great difficulty in carrying out systematic evaluation. With rapid development scale and improving requirement fine management, an urgent need to build evaluation method WNOS. By using idea big data analysis, collecting various types from existing network, comprehensive solution built help current systematically periodically. This can further implementation...

Task clustering has been proven to be an effective method reduce execution overhead and increase the computational granularity of workflow tasks executing on distributed resources. However, a job composed multiple may have greater risk suffering from failures than single task. Our theoretic analysis simulation results demonstrate that can significant impact runtime performance workflows use existing policies ignore failures. We therefore propose two general failure modeling frameworks (task...

Accurate traffic matrix estimation is critical to solving many networking problems, such as routing and network provisioning, etc. This task in a traditional IP tackled with link load measurements. But the accuracy of an approach low because underlying system linear equations governing problem highly under-determined this approach. A software-defined (SDN) provides measurements more types flows, thus opens up new opportunities for tackling problem. Furthermore, controller SDN can dynamically...

In spatial time division multiple access wireless mesh networks, not all links can be activated simultaneously, as scheduled for transmission must satisfy the specified SINR requirements. Previously, slot assignment has been done on a link basis, where set of is selected in given slot. However, if are deep fade or have no traffic to transmit, wasted. Thus, node-based scheme was proposed, nodes transmission. Which used by node depends links' instantaneous load. Although this allows us exploit...

The validation of transaction level models described in System-level Description Languages (SLDLs) often relies on extensive simulation. However, traditional Discrete Event (DE) simulation SLDLs is cooperative and cannot utilize the available parallelism modern multi-core CPU hosts. In this work, we study SLDL execution semantics concurrent threads present a parallel approach which automatically protects communication between so that hosts becomes possible. We demonstrate significant...

Recently, the modeling and design of distributed controllers in cyber-physical systems (CPSs), which suffer from messages lost, delay variation, jitter, has gained lots research attentions. A special CPS, arbitrated networked control system (ANCS), been designed for scheduling or arbitrating networks a system. In this paper, we propose novel ANCS with dual communication channels. The proposed uses hierarchical flexible time-division multiple access (TDMA)/fixed priority policy that is based...

Private cars, i.e., the vehicles owned for private use, compose a large portion of civilian automobiles, which play an important role in metropolitan transportation. car trajectory offers us effective way to understand travel behavior cars since it is useful different application areas under urban environment such as path discovery, analysis and transportation planning. The existing works regarding big data mainly concern floating or public but few consider cars. In this paper, we focus on...

Recent years have witnessed the proliferation of Low-power Wide Area Networks (LPWANs) in unlicensed band for various Internet-of-Things (IoT) applications. Due to ultra-low transmission power and long duration, LPWAN devices inevitably suffer from high Cross Technology Interference (CTI), such as interference Wi-Fi, coexisting same spectrum. To alleviate this issue, paper introduces Partial Symbol Recovery (PSR) scheme improving CTI resilience LPWAN. We verify our idea on LoRa, a widely...