Idle Nodes Research Articles

Cooperative‐routing mechanism based on node classification and task allocation for opportunistic social networks

With the development of big data, the authors have witnessed the great success of the mobile internet that the number of intelligent mobile devices (MDs) has increased dramatically and the data that needs to be transmitted grows exponentially. The traditional end-to-end communication mechanism in social networks is difficult to satisfy enormous communication demands. Therefore, opportunistic social networks proposed that message applications should choose relay nodes to perform effective data transmission processes. Currently, some routing algorithms that utilise contextual information associated with nodes need to handle heavy computing tasks and manage large numbers of messages, which usually results in higher network overhead and network latency. Furthermore, the computing power of MDs is usually limited, message carriers may not be able to quickly find the suitable relay node because of their insufficient computing power, resulting in higher network latency and network overhead. In this study, they construct a cooperative-routing mechanism based on node classification and task allocation for opportunistic social networks. In their proposed strategy, the reliable relay nodes can be obtained by classifying nodes according to the social attributes of the nodes. The task of node classification will be uniformly assigned to other idle nodes according to their computing power.

Leveraging N-1 Queues to Improve the Energy Efficiency of Scalable Computing

The clusters in a blockchain computing system can be constructed to be elastic, thus supporting scalable computing and improving energy efficiency. To form an elastic cluster, the service nodes are dynamically divided into the working nodes and the reserved nodes. Specifically, the working nodes are active to meet the computing requirements of workloads, while the reserved nodes are switched to a low-power state for energy saving. Traditionally, workloads are distributed to working nodes in the mode of N-N service queues. But in this mode, the Quality of Service (QoS) of different working nodes may be diverse, because the requirements are various for the accumulated requests in different working nodes. As a result, the overall system capability is not sufficiently utilized, and the overall system QoS is dragged down. In this paper, we propose an N-1 queueing and on-demand resource provisioning method to process workloads in the mode of N-1 service queues. Different from N-N service queues, N-1 service queues prohibit the accumulation of requests in working nodes. Thereby, once there are idle working nodes, waiting requests can immediately be delivered to them. As a result, all the working nodes are sufficiently utilized, and the overall QoS is improved. Accordingly, after using the N-1 service queues, fewer working nodes are enough to meet the same Service Level Agreement (SLA) on same workloads. In addition, by using a resource demand monitor module, our method dynamically readjusts the number of working nodes to match workload demand. Finally, the energy efficiency of an elastic cluster can be measurably improved, due to that fewer working nodes are powered on while the same SLA can be met.

A low cost paging scheme for clustered PMIPv6 protocol by head-MAG entity utilisation

Clustered PMIPv6 (CPMIPv6) was proposed to reduce the PMIPv6 signalling cost by dividing the domain into clusters each with a Head-MAG used to control the intra-cluster operations. However, existing mobility protocols perform registration process even for idle nodes, which leads to degrade the protocol performance due to unnecessary location updates. On the other hand, paging technique is widely used in cellular networks to reduce the signalling required for idle nodes registration. Although several paging schemes were proposed to enhance the PMIPv6 performance, they are either based on central entity or they incur high signalling cost due to multicasting. Inspired by CPMIPv6 architecture, this paper proposes a low cost paging scheme where each cluster is considered as a paging area and head-MAGs entities are utilised to perform the paging functions within the cluster. The analytical results show that the proposed scheme outperforms the existing paging schemes in terms of paging signalling cost.

A low cost paging scheme for clustered PMIPv6 protocol by head-MAG entity utilisation

Clustered PMIPv6 (CPMIPv6) was proposed to reduce the PMIPv6 signalling cost by dividing the domain into clusters each with a Head-MAG used to control the intra-cluster operations. However, existing mobility protocols perform registration process even for idle nodes, which leads to degrade the protocol performance due to unnecessary location updates. On the other hand, paging technique is widely used in cellular networks to reduce the signalling required for idle nodes registration. Although several paging schemes were proposed to enhance the PMIPv6 performance, they are either based on central entity or they incur high signalling cost due to multicasting. Inspired by CPMIPv6 architecture, this paper proposes a low cost paging scheme where each cluster is considered as a paging area and head-MAGs entities are utilised to perform the paging functions within the cluster. The analytical results show that the proposed scheme outperforms the existing paging schemes in terms of paging signalling cost.

On-demand resource provision based on load estimation and service expenditure in edge cloud environment

The trend of the Internet of Everything is deepening, and the amount of data that needs to be processed in the network is growing. Using the edge cloud technology can process data at the edge of the network, lowering the burden on the data center. When the load of the edge cloud is large, it is necessary to apply for more resources to the cloud service provider, and the resource billing granularity affects the cost. When the load is small, releasing the idle node resources to the cloud service provider can lower the service expenditure. To this end, an on-demand resource provision model based on service expenditure is proposed. The demand for resources needs to be estimated in advance. To this end, a load estimation model based on ARIMA model and BP neural network is proposed. The model can estimate the load according to historical data and reduce the estimation error. Before releasing the node resources, the user data on the node need to be migrated to other working nodes to ensure that the user data will not be lost. In this paper, when selecting the migration target, the three metrics of load balancing, migration time consumption and migration cost of the cluster are considered. A data migration model based on load balancing is proposed. Through the comparison of experimental results, the proposed methods can effectively reduce service expenditure and make the cluster in a state of load balancing.

Deterministic Dual-stack Query Tree RFID tag anti-collision algorithm

Tag collision problems are a major issue affecting the performance of RFID systems. The probabilistic tag anti-collision algorithm has tag starvation and cannot identify some tags. This paper proposes a deterministic dual-stack query tree algorithm (DDQT). It successfully implements the anti-collision algorithm of tags by generating new query codes and tag identification functions. At the same time, the DDQT algorithm greatly saves memory space by adding a prefix code stack and a suffix code stack. The DDQT algorithm is simple, and there is no limit on the length of the electronic tag to be queried. Compared with the previous query-tree algorithms, the DDQT algorithm has obvious improvements in query comparison times, empty query times, and occupied memory space. It can effectively remove idle nodes, shorten recognition time and save memory resources, thus improving the speed and accuracy of label recognition to some extent.

Fuzzy based energy efficient underwater routing protocol

The routing protocol in the underwater wireless sensor network is very challenging over the traditional network. Sensor nodes are placed in a specified location with their limited energy and hence the performance of the networks is affected like network lifetime and successful packet delivery. Most of the time idle sensor nodes are emitted battery power and when any target is found at that time nodes are not capable of sense and forward ability. To overcome this situation, we proposed a model for fuzzy based cluster head selection that enhances the lifetime of the network. After that we have designed a fuzzy based routing protocol which improves the packet delivery rates significantly. In compared with the existing routing protocol, we have proper utilization of energy consumption and hens it extends the overall performance of the network to overcome challenges in underwater.

Dynamic Load Balancing Based on Genetic Algorithm

Load balancing has been the focus of research over the current days in many domains but more importantly they are crucial for distributed computing. The research mainly focuses towards distributing load based on the current usage of nodes to facilitate effective resource utilization and obtain better performance from the system. Balancing load is to distribute the tasks on to the available or idle nodes so that resources are utilized fairly in a distributed environment. By developing strategies to assign the processes on a heavily loaded processor to an idle/under loaded processor in a way that balances out the load, the total processing time can be reduced hence achieving improved processor utilization. Genetic Algorithm(GA) is a search based approach that is robust and that can adapt to the search space for optimizing the solution are gaining immense popularity. GA in the proposed work considers the load as a parameter to evaluate fitness of the strings. The strings are also generated based on the load information of the nodes. The fitness evaluates the strings to identify only the underutilized or idle nodes which can take the transmitted load. Hence the work proposed explores and illustrates how GA could be employed to solve the problem of dynamic load-balancing.

Energy-efficient scheme based on user task characteristic in virtual cloud platform

Focus on node cloud computing environment due to the randomness of the user task arrival caused a large number of idle energy consumption. To solve this problem, a dynamic energy-efficient scheme in virtual machines based on user task characteristic is proposed. First, according to the amount of user tasks arrival and the expectations of task completion time, user tasks characteristic information table is established. Thus it can predict the request arrival probability and user expect to reach the finish time. Then, according to user expectations of completion time, psychological expectations QOS value of the user is obtained, and the threshold based on the integration of energy-saving value is dynamically adjusted. Finally, it can achieve energy-saving by dynamic integrating of the user task arrival rate and closing idle node. Experimental results show that the method can reach a better balance of performance and energy saving to meet user requirement.

Performance analysis and optimisation of wireless powered decode‐and‐forward considering circuit power consumption

Idle nodes are used in cooperative communications to achieve diversity gain or coverage extension. Energy harvesting (EH) allows cooperative communications to be less dependent on batteries. In this study, the performance of EH decode-and-forward relaying is analysed in terms of achievable rate for non-ideal relaying nodes whose circuit power cannot be neglected. Two time switching protocols, continuous time switching and discrete time switching, are studied. The analytical expressions for the achievable rate are derived and optimised. Numerical results show the validity of the analytical expressions and determine the influence of the circuit power consumption.

Outage Constrained Secrecy Rate Maximization for MIMOME Multicast Wiretap Channels

In this letter, we investigate a robust transmit optimization design based on an artificial noise (AN)-aided precoding scheme for maximizing secrecy rate in a multiple-input multiple-output multiple-eavesdropper multicast network where a transmitter sends confidential information to multiple intended users and provides energy for multiple idle nodes while multiple passive eavesdroppers try to overhear the secret information. Supposing Gaussian CSI uncertainties, the proposed outage-constrained secrecy rate maximization (OC-SRM) problem is nonconvex and its analytical analysis is more challenging than several existing OC-SRM schemes. Technically, to circumvent this mathematically intractable secrecy problem, we resort to low SNR approximation and some conservative approximations (e.g., Bernstein-type inequality and sphere bounding) to reformulate the OC-SRM problem into two convex subproblems which can be efficiently solved by the off-the-shelf optimization solver. Simulation results are provided to validate the security performance of the robust AN-aided precoding design.

A Game-Theoretical Modelling Approach for Enhancing the Physical Layer Security of Non-Orthogonal Multiple Access System

This paper investigates the physical layer security of a downlink non-orthogonal multiple access (NOMA) communication system, wherein a base station is communicating with two paired active users in the presence of an eavesdropper and multiple idle nodes (helpers). In order to enhance the secrecy performance, a two-phase harvest-and-jam null-steering jamming technique is deployed. In the first phase, the base station provides the helper with power in addition to active users and eavesdropper’s information via simultaneous wireless information and power transfer technique. The helpers exploit the harvested energy and the information received in the first phase to build a null-steering beamformer and jam the eavesdropper, during the information exchange between the base station and the legitimate users in the second phase. A game theory is introduced to the proposed scheme, and the base station-helpers interactions are modeled as a Stackelberg game, where the helpers play the leader role and the base station is the follower. The utility functions of both the leader and follower are formed, and the Stackelberg equilibrium is reached by means of the backward induction technique. The proposed scheme demonstrates better secrecy performance when compared with the artificial noise-aided secure NOMA system.

Priority scheduling with consolidation based backfilling algorithm in cloud

In cloud computing, scheduling plays an eminent role while processing enormous jobs. The paralle jobs utmost need parallel processing capabilities which leads to CPU underutilization mainly due to synchronization and communication among parallel processes. Researchers introduced several algorithms for scheduleing parallel jobs namely, Conservative Migration Consolidation supported Backfilling (CMCBF) and Aggressive Migration Consolidation supported Backfilling (AMCBF). The greatest challenge of a existing scheduling algorithm is to improve the data center utilization without affecting job responsiveness. Hence, this work proposes an Effective Multiphase Scheduling Approach (EMSA) to process the jobs. In EMSA, the jobs are initially preprocessed and batched together to avoid starvation and to mitigate unwanted delay. Later, an Associate Priority Method has been proposed which prioritizes the batch jobs to minimize the number of migrations. Finally, the prioritized jobs are scheduled using Priority Scheduling with BackFilling algorithm to utilize the intermediate idle nodes. Moreover, the virtualization technology partitions the computing capacity of the Virtual Machine (VM) into two-tier VM as foreground VM (FVM) and Background VM (BVM) to improve node utilization. Hence, Priority Scheduling with Consolidation based BackFilling algorithm has been deployed in a two-tier VM that processes the jobs by utilizing the VMs effectively. Experimental results show that the performance of the proposed work performs better than other existing algorithms by increasing the resource utilization by 8%.

Preventing the impact of selfish behavior under MANET using Neighbor Credit Value based AODV routing algorithm

Mobile Ad hoc Network (MANET) nodes exchange information using the multi-hop wireless communications without the need for any pre-existing infrastructure. Routing protocols of MANET are designed with an assumption that the nodes will cooperate in routing process. To achieve high throughput and reliable communication, the nodes are expected to cooperate with each other. Routing protocol plays a crucial role in an effective communication between nodes and operates on the assumption that the nodes are fully cooperative. Due to the open structure and limited battery-based energy in MANET, some nodes may not cooperate correctly or behave maliciously and such kind of misbehavior impacts the fairness, reliability and efficiency in MANET. Previous work addressed the ways to overcome these kinds of node misbehaviors and attacks. Most of the existing works need time to analyse the neighbor traffic and decide whether a neighbor is behaving maliciously or not. Further, the existing credit-based detection mechanisms may mark a genuine idle node as a malicious node. This work addresses a simple Neighbor Credit Value based AODV (NCV-AODV) routing algorithm for the detection of selfish behavior which avoids such false detection. The proposed idea is implemented in Ad hoc On Demand Distance Vector (AODV) routing protocol and an extensive analysis on the performance of the proposed detection mechanism against the selfish behavior of some MANET nodes are conducted.

Evaluation of neighbor credit value based AODV routing algorithms for selfish node behavior detection

Mobile ad hoc networks (MANETs) nodes interchange information by means of numerous intermediate nodes without the requirement of infrastructure (Toh, Ad hoc mobile wireless networks: protocols and systems, pp 34–37, 2002). Owing to the exposed arrangement and inadequate energy of the nodes, some nodes may not involve in the routing process properly (Laay et al., IEEE Commun Surv Tutor 10(4):78–93, 2008). This leads to selfish behavior of the nodes and moreover, some nodes do not have the chance to forward the packets, so they still idle in the network. Hence, these genuine idle nodes are also considered as selfish nodes and they are avoided in the routing process. To address this issue, credit-based protocols namely Neighbor credit value based and improved Neighbor credit value based Ad Hoc on demand distance vector (AODV) routing algorithms are proposed. These two protocols are evaluated against AODV for the better detection of selfish node behavior. Earlier works addressed the methods to overwhelm selfish behavior attack but fail in performance. A simple neighbor credit value based AODV (NCV-AODV) routing protocol was proposed to avoid such false detection. Some simple assumption is made on NCV-AODV that the nodes in the network are fundamentally not malicious and only some of the new nodes may be added to behave maliciously. This improved version is called improved Neighbor credit value based AODV (iNCV-AODV) protocol is proposed. The proposed two mechanisms are implemented in AODV routing protocol. An extensive analysis of the performance of the proposed detection mechanisms against the selfish behavior attack.

Energy harvesting relaying using non‐ideal relaying node in Rician fading channels

Idle nodes are used in cooperative communication to achieve performance gains. Energy harvesting (EH) technology makes cooperative communication less dependent on batteries. In this study, the performance of EH amplify-and-forward relaying is analysed by considering the throughput for Rician fading channels and non-ideal relaying nodes, compared with previous works that focused on Rayleigh fading channels with ideal relaying nodes. The authors consider discrete time EH protocol and continuous time EH protocol. In addition, they derive the analytical expressions for the average throughput. Numerical results are presented to show the good performance of the system in Rician fading channels and the satisfactory performance while using the non-ideal relaying node by examining various system parameters using the analytical expressions.

LB-networks: A model for dynamic load balancing in queueing networks

Dynamic load balancing plays an important role in the management of data centres where a fair workload distribution may be hard to achieve. Dynamic load balancing algorithms are usually clustered into two families: receiver-initiated and sender-initiated. In the former approach, an idle node transfers some of the jobs of a highly loaded node to its queue, whereas in the latter it is the overloaded node that decides to send somewhere else some of the jobs that have been assigned to itself. The literature has proved the receiver-initiated strategies to be more effective than the sender-initiated ones under heavy load. In this paper, we give for the first time a closed form expression of the stationary distribution of a class of queueing networks where an arbitrary number of nodes implement a receiver-initiated dynamic load balancing algorithm. The result can be applied to Markovian queueing networks with probabilistic routing and exponentially distributed service times.

Energy-Efficient Algorithms for Dynamic Virtual Machine Consolidation in Cloud Data Centers

Cloud computing has become a significant research area in large-scale computing, because it can share globally distributed resources. Cloud computing has evolved with the development of large-scale data centers, including thousands of servers around the world. However, cloud data centers consume vast amounts of electrical energy, contributing to high-operational costs, and carbon dioxide emissions. Dynamic consolidation of virtual machines (VMs) using live migration and putting idle nodes in sleep mode allows cloud providers to optimize resource utilization and reduce energy consumption. However, aggressive VM consolidation may degrade the performance. Therefore, an energy-performance tradeoff between providing high-quality service to customers and reducing power consumption is desired. In this paper, several novel algorithms are proposed for the dynamic consolidation of VMs in cloud data centers. The aim is to improve the utilization of computing resources and reduce energy consumption under SLA constraints regarding CPU, RAM, and bandwidth. The efficiency of the proposed algorithms is validated by conducting extensive simulations. The results of the evaluation clearly show that the proposed algorithms significantly reduce energy consumption while providing a high level of commitment to the SLA. Based on the proposed algorithms, energy consumption can be reduced by up to 28%, and SLA can be improved up to 87% when compared with the benchmark algorithms.

Overhearing-Based Co-Operation for Two-Cell Network With Asymmetric Uplink-Downlink Traffics

In this paper, a new transmission protocol is proposed for a two-cell network, where each cell, respectively, has one-uplink and one-downlink data traffic requirement. By designing bidirectional relaying protocol, which admits the idle nodes to overhear the interference sent by the other nodes, the spectral efficiency can be greatly improved. The proposed overhearing transmission protocol provides a new principle that converts the overheard interference from the negative role to the positive contribution for the desired signal to interference plus noise ratio (SINR) enhancement via various transmit and receive schemes.} In order to enhance the quality of the desirable link, an adaptive receiver consisting of both the minimum mean squared error (MMSE) and MMSE successive interference cancelation (SIC) techniques is proposed. Based on the proposed transmission structure, the precoding is further optimized for the multiantenna relay to maximize the weighted sum-rate of all data traffics with the limited power constraint. At last, simulations verify the gains obtained from the proposed protocol and the optimized relaying precoder.

Localized paging in proxy mobile IPv6 networks

In Proxy Mobile IPv6 (PMIPv6) networks, proxy registrations are performed even for idle mobile nodes (MNs), resulting in unnecessary signaling traffic and protocol cost. Although there have been many paging techniques aimed at reducing the unnecessary location updates, those are mainly focused on telecommunication systems and how to adopt IP paging schemes in PMIPv6 is not yet well studied. In this paper, we introduce a new paging scheme that optimizes paging performance in a localized manner. The proposed localized paging scheme pages the idle MN through a mobility access gateway (MAG) while the operation is transparent to a local mobility anchor (LMA) in a PMIPv6 network domain. In this way, a bottleneck risk at the LMA can be avoided, without a huge requirement of buffer size and paging singling cost. We develop a thorough analytical model for evaluating the performance of the proposed scheme, compared with a LMA-based paging scheme in terms of the buffer size requirement and signaling cost. Analytical results demonstrate that the proposed paging scheme can significantly reduce the signaling cost for PMIPv6, achieving a less buffer size requirement and of course shorter paging delay, compared with those of the LMA-based paging scheme.