International Journal of Grid and High Performance Computing
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Wireless sensor networks (WSN) deployed in open environments make nodes prone to various security attacks due to their resource constrained nature. The compromised nodes are used to mislead the sensed data and disrupt communication, which can affect the entire decision-making system based on the sensed data. It is also possible to drain the sensor nodes energy and reduce the battery life of the networks. Trust models are the preferred mechanism to secure WSN. In this paper, the authors present communication trust and energy aware (CTEA) routing protocol that make use of the proposed trust model to mitigate the effects of badmouth and energy drain attacks. They use Dempster theory to compute communication trust and also consider the energy metric, to establish the route for data transfer. The simulation result shows that the proposed trust model increases the packet delivery ratio, residual energy, and network lifetime by mitigating the nodes misbehaviour in presence of energy drain and bad mouth attacks.

Cloud computing is a quickly emerging computing model in the IT industry. Due to the rapid increase in technology, many clients want to store multiple copies of the same data in multiple data centers. Clients are outsourcing the data to cloud service providers and enjoying the high quality of service. Cloud service providers (CSP) are going to charge extra amounts for storing multiple copies; CSP must provide the firm guarantee for storing multiple copies. This paper proposes a new system model for storing and verifying multiple copies; this model deals with identifying tarnished copies which are transparent for the clients. Also, it deals with dynamic data control in the cloud with optimal results.

Cloud computing is a booming technology in the area of digital markets. Tackling the nonfunctional characteristics is a big challenge between service consumers (SC) and service providers (SP). Without proper negotiation between the participants specifying their quality of service (QoS) requirements, service level agreement (SLA) cannot be achieved. Two strategies that are commonly prevalent in the negotiation process are concession model and trade off model. The concession model assures the service consumer (SC) receiving the services on time without any deferment. But service consumer has only limited utility. To balance the utility and achievement rates, the authors propose a mixed negotiation approach for cloud service negotiation, which is based on “Game of Chicken.” Extensive results show that a mixed negotiation approach brings equal amount of satisfaction to both service consumer and service provider in terms of achieving higher utility and outperforms the concession approach, while taking fewer time delays than that of a tradeoff approach.

Cognitive radio networks (CRNs) deal with sensing, decision making, sharing, and mobility. Among these aspects, spectrum mobility assumes a vital role for spectrum handoff to occur. When the spectrum handoff process is analyzed, there are call drops, spectrum handoff, and interferences with the adjacent channels. For minimizing the handoff of the spectrum's probability as well as the call drops, which involves three processes, which are followed in sequential order, results demonstrate a better QoS. In the following three processes, the first process starts with the Markov model that identifies a channel's states and selects the channel which is apt. The second process, multiple attributes decision making (MADM), methods choose one of the best possible channels among all the channels based on various metrics in the proposed hybrid method. In the third process, the spectrum handoff is analyzed through different distribution models to indicate which model is the desirable one for a handoff process such as the one with stationary users or the other with non-stationary users.

One of the treading technologies in the field of data processing and communication is internet of things. To make life a lot easier for the disabled and visually impaired people, IoT can offer assistance and support in various ways. Visually impaired (VI) is a term used to describe any kind of sight loss; some people are completely blind, but many others have legal blindness. The proposed system visually impaired-quality of life (VI-QOL) consists of Arduino UNO, ultrasonic sensors, proximity sensors, and some of the IoT components along with smartphone. Using these components, the author's research goal is to improve the mobility of VI people in a wider range of travel activities. The proposed VI-QOL framework tested all the consequences of IoT components and the Android applications. Total transaction time for navigation system of the proposed solution is measured with and without any load in the application, which proves the efficiency of the proposed work. The throughput of the proposed solution is proved to be high.

NVMe SSDs are deployed in data centers for applications with high performance, but its capacity and bandwidth are often underutilized. Remote access NVMe SSD enables flexible scaling and high utilization of Flash capacity and bandwidth within data centers. The current issue of remote access NVMe SSD has significant performance overheads. The research focuses on remote access NVMe SSD via NTB (non-transparent bridge). NTB is a type of PCI-Express; its memory mapping technology can allow to access memory belonging to peer servers. NVMe SSD supports multiple I/O queues to maximize the I/O parallel processing of flash; hence, NVMe SSD can provide significant performance when comparing with traditional hard drives. The research proposes a novel design based on features of NTB memory mapping and NVMe SSD multiple I/O queues. The remote and local servers can access the same NVMe SSD concurrently. The experimental results show the performance of remote access NVMe SSD can approach the local access. It is significantly excellent and proved feasible.

The interest in cloud computing and its techniques are gaining exponentially in IT industries because of its cost-effective architecture and services. However, these flexible services of cloud bring many security and privacy challenges due to loss of control over the data. This paper focuses on an analysis of various computational trust models in cloud security environment. The computational trust models that are used to build secure cloud architectures are not available in a blended fashion to overcome security and privacy challenges. The paper aims to contribute to the literature review to assist researchers who are striving to contribute in this area. The main objective of this review is to identify and analyse the recently published research topics related to trust models and trust mechanisms for cloud with regard to research activity and proposed approaches. The future work is to design a trust mechanism for cloud security models to achieve the higher level of security.

As the application of network encryption technology expands, malicious attacks will also be protected by encryption mechanism, increasing the difficulty of detection. This paper focuses on the analysis of encrypted traffic in the network by hosting long-day encrypted traffic, coupled with a weighted algorithm commonly used in information retrieval and SSL/TLS fingerprint to detect malicious encrypted links. The experimental results show that the system proposed in this paper can identify potential malicious SSL/TLS fingerprints and malicious IP which cannot be recognized by other external threat information providers. The network packet decryption is not required to help clarify the full picture of the security incident and provide the basis of digital identification. Finally, the new threat intelligence obtained from the correlation analysis of this paper can be applied to regional joint defense or intelligence exchange between organizations. In addition, the framework adopts Google cloud platform and microservice technology to form an integrated serverless computing architecture.

The deployment of an automatic network performance measurement system is crucial to the early detection and analysis of network quality degradations and failures. Once the overall network health status can be summarized and visualized in an easily accessible graphic user interface, the difficulty of network maintenance and troubleshooting can be significantly reduced. This study provided a detailed introduction to how the perfSONAR is implemented in TWAREN backbone and how the individual data are integrated and eventually visualized as a handy weathermap for network operators to use.

Wireless sensor networks are used in machine learning for data communication and classification. Sensor nodes in network suffer from low battery power, so it is necessary to reduce energy consumption. One way of decreasing energy utilization is reducing the information transmitted by an advanced machine learning process called support vector machine. Further, nodes in WSN malfunction upon the occurrence of malicious activities. To overcome these issues, energy conserving and faulty node detection WSN is proposed. SVM optimizes data to be transmitted via one-hop transmission. It sends only the extreme points of data instead of transmitting whole information. This will reduce transmitting energy and accumulate excess energy for future purpose. Moreover, malfunction nodes are identified to overcome difficulties on data processing. Since each node transmits data to nearby nodes, the misbehaving nodes are detected based on transmission speed. The experimental results show that proposed algorithm provides better results in terms of reduced energy consumption and faulty node detection.