Capabilities Of Nodes Research Articles

ETRT – Cross layer model for optimizing transmission range of nodes in low power wireless networks – An Internet of Things Perspective

Internet of Things network is managed by battery operated devices and low power radio links since they are referred to low power networks. In present communication era, many research works are concentrating on low power wireless network. Cross layer design is one of the acclaimed technique that decidedly improves the network performance. In this article, we come up with the cross-layer model that satisfies distinct network requirements and prolongs network lifetime. It integrates physical layer, data link layer (Media Access Control) and network layer in the protocol stack. In our model, a threshold value called ETRT (Expected Transmission Range Threshold) is introduced, which is computed with the help of routing information. Later, MAC based power control technique utilizes the ETRT value and assigns optimum transmission range for every node. The idea at the heels of proposed cross layer model is estimating the capability (ETRT value) of the particular node and assigning the suitable transmission power for every node, based on its capability (ETRT value). Hence, assigning optimum transmission power based on ETRT information prolongs the network lifetime with better reliability and Quality of Service(QoS). From our results, it is noticed that the ETRT based cross layer model performs twice better than the standard model.

DDoS Attacks Detection and Prevention in Mobile Adhoc Network: A Survey

Ad-hoc system is a gathering of wireless movable nodes enthusiastically creating a momentary network lacking the use of any core-existing centralized administration or network infrastructure. MANET has some limitations owing to infrastructure, mobility, capabilities of mobile nodes or due to system as a whole. Limitations due to infrastructure or system, Broadcast nature of communications, frequent disconnections / partitions, Limited bandwidth, packet loss due to transmission error, variable capacity links. Cooperative procedures, Exposed medium, dynamically varying system topology, inadequacy of centralized monitoring, Nonexistence of clear line of resistance. There is no layered security in MANETs like in wired network. Data packets routed between a sender node (source) and a receiver node (destination) of a MANET often traverse along a path spanning multiple links, which is known as the multihop path. The paper provides survey to DDoS attacks prevention and detection methods.

Context-Aware Task Migration for HART-Centric Collaboration over FiWi Based Tactile Internet Infrastructures

Low task execution time and low energy consumption of collaborating mobile human users and robots are important requirements of emerging human-agent-robot teamwork (HART)-centric Tactile Internet applications. In particular, task migration among mobile HART members has emerged as an important research topic, taking different task types, task deadlines, collaborative node capabilities, and mobility patterns into account. We propose a context-aware task migration scheme for efficiently orchestrating the real-time collaboration among human mobile users, central and decentralized computational agents (cloud/cloudlets), and collaborative robots (cobots) across converged fiber-wireless (FiWi) communications infrastructures. We investigate the problem of whether and, if so, when and where a HART-centric task should be best migrated to. For resource-efficient task execution, the migration decision is made according to given task processing capabilities of cloud/cloudlet agents and cobots, task execution deadline, energy consumption of involved cobots and mobile devices, and task migration latency. We evaluate the performance of our context-aware HART-centric task migration scheme and compare it to conventional task execution without migration. Towards this end, we develop an analytical framework for quantifying its performance in terms of a variety of task migration key performance metrics, including task migration gain-overhead ratio, deadline-miss ratio, task response time, and energy consumption efficiency.

LNDIR: A lightweight non-increasing delivery-latency interval-based routing for duty-cycled sensor networks

Wireless sensor networks are composed of low-energy, small-size, and low-range unattended sensor nodes. Recently, it has been observed that by periodically turning on and off the sensing and communication capabilities of sensor nodes, we can significantly reduce the active time and thus prolong network lifetime. However, this duty cycling may result in high network latency, routing overhead, and neighbor discovery delays due to asynchronous sleep and wake-up scheduling. These limitations call for a countermeasure for duty-cycled wireless sensor networks which should minimize routing information, routing traffic load, and energy consumption. In this article, we propose a lightweight non-increasing delivery-latency interval routing referred as LNDIR. This scheme can discover minimum latency routes at each non-increasing delivery-latency interval instead of each time slot. Simulation experiments demonstrated the validity of this novel approach in minimizing routing information stored at each sensor. Furthermore, this novel routing can also guarantee the minimum delivery latency from each source to the sink. Performance improvements of up to 12-fold and 11-fold are observed in terms of routing traffic load reduction and energy efficiency, respectively, as compared to existing schemes.

Clustering in Multi-Channel Cognitive Radio Ad Hoc and Sensor Networks

CR enables dynamic spectrum access to utilize licensed spectrum when it is idle. CR technology is applied to wireless ad hoc and sensor networks to form CRAHNs and CRSNs, respectively. Clustering is an efficient topology management technique to regulate communication and allocate spectrum resources by CR capabilities of nodes in CRAHNs and CRSNs. In this article, we thoroughly investigate the benefits and functionalities of clustering such as topology, spectrum, and energy management in these networks. We also overview motivations for and challenges of clustering in CRAHNs and CRSNs. Existing clustering schemes are reviewed and compared. We conclude by revealing key considerations and possible solutions for spectrum-aware clustering in multi-channel CRAHNs and CRSNs.

FEMOS: Fog-Enabled Multitier Operations Scheduling in Dynamic Wireless Networks

Fog computing has recently emerged as a promising technique in content delivery wireless networks to alleviate the heavy bursty traffic burdens on backhaul connections. In order to improve the overall system performance, in terms of network throughput, service delay and fairness, it is very crucial and challenging to jointly optimize node assignments at control tier and resource allocation at access tier under dynamic user requirements and wireless network conditions. To solve this problem, in this paper, a fog-enabled multitier network architecture is proposed to model a typical content delivery wireless network with heterogeneous node capabilities in computing, communication, and storage. Further, based on Lyapunov optimization techniques, a new online low-complexity algorithm, namely fog-enabled multitier operations scheduling (FEMOS), is developed to decompose the original complicated problem into two operations across different tiers. Rigorous performance analysis derives the tradeoff relationship between average network throughput and service delay, i.e., ${[O(1/V), O(V)] }$ with a control parameter $\boldsymbol {V}$ , under FEMOS algorithm in dynamic wireless networks. For different network sizes and traffic loads, extensive simulation results show that FEMOS is a fair and efficient algorithm for all user terminals and, more importantly, it can offer much better performance, in terms of network throughput, service delay, and queue backlog, than traditional node assignment and resource allocation algorithms.

An Efficient routing protocol for MANET

Nodes in MANET are mobile with limited capacities. The nodes are energy constraint in MANET which limits the routing capability of nodes and network lifetime. Therefore to improve performance of MANET, special routing algorithms which can establish energy efficient path to route packets from source to destinations are needed. If the selected route is energy efficient, it can maximize the throughput, minimize delay and can also increase network lifetime. But establishing energy efficient route between source and destination is itself difficult task. In this paper, an effort has been done to increase network lifetime and throughput by proposing a new energy efficient protocol. This protocol provides energy efficient route by considering residual energy of intermediate nodes. This paper shows that proposed protocol improves network lifetime as well as throughput and reduces delay compared to AODV.

Two-Tier Device-Based Authentication Protocol Against PUEA Attacks for IoT Applications

Securing Internet of Things (IoT) applications is complicated by the limited power and processing capabilities of a typical sensor node. This paper proposes a protocol and a method of spectrum management that can guard against common types of security threats despite the limitations of the local processing. With a hierarchical cognitive IoT architecture, this paper incorporates the strengths of cognitive radio and the physical properties of a device to improve the performance of a cognitive radio sensor network (CRSN) and resolve the security problem, considering one of the most destructive attacks in CRSNs called the primary user emulation attack (PUEA). Accordingly, for delivering trustable services, we explore the tradeoff between spectrum management and the successful detection rate of malicious nodes. The proposed distributed secure algorithm allows the sensing sensors and the tasking nodes to perform a detection and identification mechanism such that dynamic spectrum management and correct spectrum decision can be achieved. The experimental results show that the proposed secure system provides a significant protection against the PUEA attacks.

Serum levels of testosterone and SHBG in association with body mass index improve the predictive capability of consolidate tumor biomarkers in pre- and postmenopausal breast cancer patients.

To investigate the contribution of serum levels of testosterone (TS) and sex hormone binding globulin (SHBG) in association with body mass index (BMI) as a surrogate marker of obesity, to the predictive capability of tumor size (T), lymph node (N) and estrogen receptor (ER) status and proliferative activity (TLI). We investigated 120 women with primary breast cancer and median follow-up of 138 months. Serum levels of TS and SHBG and patient's BMI were evaluated before surgery. The contribution of TS, SHBG, their ratio (TS/SHBG) and BMI to the predictive capability of tumor-specific biomarkers was investigated by Harrell's c statistic. TS alone did not affect prognosis, whereas SHBG was protective in postmenopausal patients, in which BMI was associated with a progressive increase in the relapse-specific hazard ratio (HR). When in combination, TS, SHBG and BMI, affected prognosis in different ways depending on menopausal status. The best predictive capability (c = 0.78) was observed in postmenopausal patients when at the basic model (N + TLI) were added TS, BMI, TS * BMI interaction, with or without SHBG. In premenopause subgroup, the best predictive capability (c = 0.67) was provided by the basic model (N + TLI) plus TS and SHBG or their ratio, BMI and TS * BMI or TS/SHBG * BMI interaction. Patient-associated features such as BMI and serum levels of TS and SHBG can improve the predictive capability of consolidate tumor-specific biomarkers in both pre- and postmenopause, thus providing a relevant contribution to the decision-making process.

Energy-Efficient Two-Layer Cooperative Defense Scheme to Secure Sensor-Clouds

Sensor-cloud computing is envisioned as a promising technology that can integrate various services by extending the computational capabilities of physical sensor nodes. It is prone to attack because of special characteristics of physical sensor nodes and virtual sensor-service nodes. Considering the intrusion detection threshold, false alarm probability of the intrusion detection system (IDS), and three different attacked scenarios, we devise a physical IDS (PIDS)-to-gateway and virtual IDS (VIDS)-to-gateway detection model for Sensor-Cloud. We formulate a two-layer gateway-assisted detection and defense decision problem involving multiple IDSs using an evolutionary game in order to optimize the intrusion detection strategy for lowering energy consumption and reducing alarm messages. We derive an evolutionary stable strategy and prove that the proposed mechanism achieves Nash equilibrium, such that each IDS completes cooperatively defense tasks. We propose a game-theoretic approach to achieve an energy-efficient cooperative defense scheme for sensor-cloud computing environments. The simulation results demonstrate that the proposed mechanism achieves energy-efficient defense and increases security of data in the Sensor-Cloud.

Evaluation across and within collaborative manufacturing networks: a comparison of manufacturers’ interactions and attributes

Evaluation on collaborative manufacturing network (CMN) structure characteristics has important implications for network operations such as production decision-making, product recovery, creating consensus. Several recent studies suggest that augmenting network structure with nodes’ attributes can provide a more fine-grained understanding of the network. However, there have been few studies to provide a systematic understanding of these effects in a CMN at scale. This gap is bridged using an industrial printing machinery CMN data-set collected on a web-based producing and outsourcing service platform. Novel phenomena with respect to both interaction and attribute metrics across and within the CMNs are observed. Moreover, although many studies employ either interaction or attribute data to study the relative roles of manufacturers in a CMN, relatively little is known about the relationship between these two types of data. This study explores this relationship by comparing two defined metrics (i.e. relational capability and node capability), which evaluate the manufacturers’ interactions and attributes, respectively. We examine to what extent the two metrics of manufacturers correlate with each other, and how possible dissimilarities and similarities can be explained based on the collected industrial CMN data-set. The insights thereby provide a better basis for efficient operations decision-making in CMN.

Optimal day‐ahead demand response contract for congestion management in the deregulated power market considering wind power

In the liberalised electricity market, congestion management (CM) with a high penetration of wind energy is a challenging task for Independent System Operators (ISOs). Even though demand response (DR) provides an opportunity to alleviate transmission congestion, strategic selection of aggregated loads to contract with for DR in the day-ahead economic dispatch is still under-investigated. To solve this problem, this study proposes a bi-level optimisation model to determine the optimal DR buses for CM in the day-ahead market considering the uncertainty of wind power. The upper model serves to compute the available transfer capability (ATC), while the lower model is to calculate the stochastic dynamic optimal power flow. Through converting the stochastic ATC values to a summation of load supply capability of each load node, the loads which will deteriorate transmission congestion if the corresponding demand grows are determined. The corresponding loads with DR are selected as the optimal candidates. Furthermore, this study constructs a two-stage optimisation model for optimal load dispatch by incorporating both price-based DR and incentive-based DR. The result can be used to assist system operators in decision-making of electricity biddings from DRs for load curtailment and shift in the market clearing. As a result, the difference of peak and valley loads is reduced; ISOs as well as DR participators can both get economic benefits. Simulation results from the PJM 5-bus training system and the modified IEEE 30-bus system demonstrate the effectiveness of the proposed algorithm for DR contracting in CM.

Performance Optimization and Parallelization of a Parabolic Equation Solver in Computational Ocean Acoustics on Modern Many-core Computer

As one of open-source codes widely used in computational ocean acoustics, FOR3D can provide a very good estimate for underwater acoustic propagation. In this paper, we propose a performance optimization and parallelization to speed up the running of FOR3D. We utilized a variety of methods to enhance the entire performance, such as using a multi-threaded programming model to exploit the potential capability of the many-core node of high-performance computing (HPC) system, tuning compile options, using efficient tuned mathematical library and utilizing vectorization optimization instruction. In addition, we extended the application from single-frequency calculation to multi-frequency calculation successfully by using OpenMP+MPI hybrid programming techniques on the mainstream HPC platform. A detailed performance evaluation was performed and the results showed that the proposed parallelization obtained good accelerated effect of 25.77X when testing a typical three-dimensional medium-sized case on Tianhe-2 supercomputer. It also showed that the tuned parallel version has a weak-scalability. The speed of calculation of underwater sound field can be greatly improved by the strategy mentioned in this paper. The method used in this paper is not only applicable to other similar computing models in computational ocean acoustics but also a guideline of performance enhancement for scientific and engineering application running on modern many-core-computing platform.

Optimal Task Scheduling for Distributed Cluster With Active Storage Devices and Accelerated Nodes

With advancements in compute-intensive and memory-bound applications, the need for faster and more energy-efficient processing platforms continues. In support of these advancements, heterogeneous platforms have been proposed to enhance the performance and efficiency in the cloud. These platforms include field programmable gate arrays and graphical processing units in addition to general-purpose processors. Furthermore, there is a strong interest in advancing active solid-state drives to support both storage and computation. In this paper, we present a generic formulation to support the modeling of such a heterogeneous cloud environment, without being specific to a particular cloud platform such as Spark or Hadoop. We represent the cloud as a collection of clients, middleware control nodes, and high performance compute nodes (HPN), where the HPNs represent the options of advanced compute technologies in a heterogeneous cloud. The objective of the paper is to present a simple and efficient formulation for scheduling applications in such a heterogeneous cloud. Consistent with recent software modeling of artificial intelligence applications, we propose to map applications into directed acyclic graph representations of tasks. The optimization problem is then formulated to infer the best scheduling of tasks on the HPNs, while minimizing the overall execution time and data communication delays between nodes. Unlike existing scheduling algorithms that assume equal performance across nodes, our formulation explicitly takes into account the different compute capabilities of the heterogeneous nodes. The resulting task scheduling is then evaluated to provide insights into the performance gains with the proposed advanced heterogeneous cloud computing environment. The results show improved performance when comparing the proposed task-scheduling algorithm with the genetic algorithm and heterogeneous earliest finish time algorithms. We also show the performance gains achieved with the optimal task scheduling on a heterogeneous cloud system as compared with a conventional CPU-only cloud system.

Radio Resource Allocation for Achieving Ultra-Low Latency in Fog Radio Access Networks

Fog radio access network (F-RAN) has the significant advantages of local radio signal processing, cooperative radio resource management, and distributed storage capability to tackle the massive users demand at the edge. However, due to constrained fronthaul capacity, achieving ultra-low latency for emerging cellular networks is still challenging. This paper focuses on alleviating the heavy burden on fronthaul and achieving ultra-low latency by proposing a loosely coupled architecture in the F-RAN where a large number of F-RAN nodes are able to participate in joint distributed computing and content sharing regardless of nearness communication by satisfying the minimum latency demand. A mixed-integer nonlinear programming problem is formulated to achieve the ultra-low latency under the constraint of fronthaul capacity and computing capability of each F-RAN node. To solve this problem, a joint distributed computing scheme and a distributed content sharing scheme are proposed with the greedy algorithm to find a sub-optimal solution, in which the weighted minimum mean square error approach is adopted to optimize the transmission rate. Numerical results reveal that the ultra-low latency can be achieved in F-RANs by properly utilizing the loosely coupled architecture.

Consistent and effective energy utilisation of node model for securing data in wireless sensor networks

This paper introduces the new routing model called Effective Energy Utilisation of Node Model (EEUNM) created for energy-efficient and secure data in wireless sensor networks. EEUNM deals with wireless sensor applications such as military and forest field. The aim of this model is to find the perfect path based on consumption of node energy. The focus of EEUNM is a new approach to simultaneously factor energy and trustworthiness of routes in the routing model. EEUNM finds and selects the path on the basis of having maximum capability of node with incurring additional cost in overhead compared to the common protocols AODV-EHA and LTB-AODV. In this work, simulation results show that the proposed model EEUNM keeps the same security level while completing better energy utilisation of nodes for data packet delivery.

Consistent and effective energy utilisation of node model for securing data in wireless sensor networks

This paper introduces the new routing model called Effective Energy Utilisation of Node Model (EEUNM) created for energy-efficient and secure data in wireless sensor networks. EEUNM deals with wireless sensor applications such as military and forest field. The aim of this model is to find the perfect path based on consumption of node energy. The focus of EEUNM is a new approach to simultaneously factor energy and trustworthiness of routes in the routing model. EEUNM finds and selects the path on the basis of having maximum capability of node with incurring additional cost in overhead compared to the common protocols AODV-EHA and LTB-AODV. In this work, simulation results show that the proposed model EEUNM keeps the same security level while completing better energy utilisation of nodes for data packet delivery.

Achieving efficiency in autonomic network management of IP networks based on SDN management logic

The layer-three redundancy in large companies' IP networks remains a major concern, aiming to increase, as much as possible, the availability ratio for the offered services to the customers. However, deploying the existing protocols requires in addition to providing backup links and physical equipment, the manual configuration which is time-consuming and error-prone. Autonomic router redundancy controller (ARRC) was the first autonomic solution whose objective was to deploy redundancy on existing networks. Yet, this solution was unable to handle redundancy in all network scenarios. In this paper, we propose a new approach extended ARRC (E-ARRC), inspired from software defined networking (SDN) management logic to address ARRC shortcomings and limitations. SDN represents a new vision for the future networks, aiming to reduce complexity and to ensure an efficient control of the network behaviour. Based on a global view of the network, SDN achieves business needs via a high-level specification of rules which are applied accordingly on the SDN capable nodes. The results of our approach, which is based on shared-networks reachability, illustrate a more granular level of redundancy, with a reliable exploitation of all the available resources.

Key establishment scheme for wireless sensor networks based on polynomial and random key predistribution scheme

Establishing communication keys for pairs of neighbouring sensor nodes is the foundation of the security in wireless sensor networks (WSNs). However, due to the resource constraints on nodes, this task is challenging for the constrained memory, energy, and computational capabilities of sensor nodes. This paper proposes a novel key predistribution scheme based on the polynomial pool-based key predistribution scheme and random key predistribution. In the proposed scheme, parts of the preloaded information in each sensor node are the polynomial shares and the rest of the preloaded information are the keys generated by the polynomial shares preloaded in the sensor nodes. Performance analyses and comparisons with other schemes are performed in this paper. The comparison of security results confirm that the proposed scheme has better resilience against node compromising attacks when compared to previous schemes.

An Energy Efficient Autonomous Method for Coverage Optimization in Wireless Multimedia Sensor Networks

In this paper, a distributed method for coverage optimization of random deployed WMSNs utilizing motility and mobility capabilities of nodes, is proposed. The aims followed by the method are first, maximizing the coverage ratio by minimizing both the covered overlapping areas, and the coverage holes after random deployment, and second, enhancing energy efficiency of the coverage optimization procedure, by minimizing the needed rotations and specially movements, comparing with the previous schemes. To these aims, the most appropriate location and orientation of the nodes are calculated round by round considering all the possible nested compositions of rotation and movement. But, rotating and moving the nodes are performed after terminating the algorithm rounds and achieving the decisive results. So, the proposed method does not impose the overhead of trial and error of rotation or relocation on the network nodes. The performance of the proposed approach has been compared with the previous works for different network configurations; simulation results show that the proposed approach outperforms the previous schemes in terms of both coverage ratio and energy efficiency.