The devices of the Internet of Things (IoT) are integrated and interconnected by using the traditional wireless communication technology. The unavailability of spectrum sharing occurs in traditional wireless communication due to the presence of a massive number of IoT devices. Thus, the cognitive radio network (CRN) is introduced as a promising technology to utilize the spectrum efficiently. Channel hopping sequence (CHS) is used to establish communication among CRN users. However, the majority of CHS mechanisms only focus on multiuser single-hop scenarios, which can lead to bottleneck and throughput degradation problems. It is also found that few existing CHS mechanisms still have a low percentage of rendezvous that can cause difficulties for the secondary users (SUs) to communicate. Thus, it is a challenge to design efficient CHS for establishing fast communication among SUs under multiuser, multihop scenarios, and asymmetric asynchronous environments. In this article, asymmetric synchronous and asymmetric asynchronous (ASAA) channel hopping (CH) algorithms are designed for the multiuser CRN-enabled IoT devices to share the unused spectrum in the multihop scenario. The multiuser asymmetric synchronous (MUAS) and multiuser asymmetric asynchronous (MUAA) protocols are designed in the proposed ASAA CH mechanism. The simulation results show that the proposed ASAA CHS algorithms outperform the existing CHS mechanisms in terms of throughput, channel loading (CL), channel utilization (CU), maximum time to rendezvous (MTTR), average time to rendezvous (ATTR), and maximum inter rendezvous interval (MIRI).

The applications that are deployed in the cloud to provide services to the users encompass a large number of interconnected dependent cloud components. Multiple identical components are scheduled to run concurrently in order to handle unexpected failures and provide uninterrupted service to the end user, which introduces resource overhead problem for the cloud service provider. Furthermore such resource-intensive fault tolerant strategies bring extra monetary overhead to the cloud service provider and eventually to the cloud users. In order to address these issues, a novel fault tolerant strategy based on the significance level of each component is developed. The communication topology among the application components, their historical performance, failure rate, failure impact on other components, dependencies among them, etc., are used to rank those application components to further decide on the importance of one component over others. Based on the rank, a Markov Decision Process (MDP) model is presented to determine the number of replicas that varies from one component to another. A rigorous performance evaluation is carried out using some of the most common practically useful metrics such as, recovery time upon a fault, average number of components needed, number of parallel components successfully executed, etc., to quote a few, with similar component ranking and fault tolerant strategies. Simulation results demonstrate that the proposed algorithm reduces the required number of virtual and physical machines by approximately 10% and 4.2%, respectively, compared to other similar algorithms.

In Cloud Computing, the tenants opting for the Infrastructure as a Service (IaaS) send the resource requirements to the Cloud Service Provider (CSP) in the form of Virtual Network (VN) consisting of a set of inter-connected Virtual Machines (VM). Embedding the VN onto the existing physical network is known as Virtual Network Embedding (VNE) problem. One of the major research challenges is to allocate the physical resources such that the failure of the physical resources would bring less impact onto the users’ service. Additionally, the major challenge is to handle the embedding process of growing number of incoming users’ VNs from the algorithm design point-of-view. Considering both of the above-mentioned research issues, a novel Failure aware Semi-Centralized VNE (FSC-VNE) algorithm is proposed for the Fat-Tree data center network with the goal to reduce the impact of the resource failure onto the existing users. The impact of failure of the Physical Machines (PMs), physical links and network devices are taken into account while allocating the resources to the users. The beauty of the proposed algorithm is that the VMs are assigned to different PMs in a semi-centralized manner. In other words, the embedding algorithm is executed by multiple physical servers in order to concurrently embed the VMs of a VN and reduces the embedding time. Extensive simulation results show that the proposed algorithm can outperform over other VNE algorithms.

The Hadoop enabled cloud platforms are gradually becoming preferred computational environment to execute scientific big data workloads in a periodic manner. However, it is observed that the default data placement approach of such cloud platforms is not the efficient one and often ends up with significant data transfer overhead leading to degradation of the overall job completion time. In this article, a Resource and Network-aware Data Placement Algorithm (RENDA) is proposed to reduce the non-local executions and thereby reduce the overall job completion time for periodic workloads in the cloud environment. The entire job execution is modeled as a two-stage execution characterized as data distribution and data processing. The RENDA reduces the time of the stages as mentioned above by estimating the heterogeneous performance of the nodes on a real-time basis followed by careful allocation of data in several installments to participating nodes. The experimental results show that the proposed RENDA algorithm consistently outperforms over the recent state-of-the-art alternatives with as much as 28 percent reduction in data transfer overhead leading to 16 percent reduction in average job completion time with 27 percent average speedup on average job execution.

The recent advances in virtualization technology have enabled the sharing of computing and networking resources of cloud data centers among multiple users. Virtual Network Embedding (VNE) is highly important and is an integral part of the cloud resource management. The lack of historical knowledge on cloud functioning and inability to foresee the future resource demand are two fundamental shortcomings of the traditional VNE approaches. The consequence of those shortcomings is the inefficient embedding of virtual resources on Substrate Nodes (SNs). On the contrary, application of Artificial Intelligence (AI) in VNE is still in the premature stage and needs further investigation. Considering the underlying complexity of VNE that includes numerous parameters, intelligent solutions are required to utilize the cloud resources efficiently via careful selection of appropriate SNs for the VNE. In this paper, Reinforcement Learning based prediction model is designed for the efficient Multi-stage Virtual Network Embedding (MUVINE) among the cloud data centers. The proposed MUVINE scheme is extensively simulated and evaluated against the recent state-of-the-art schemes. The simulation outcomes show that the proposed MUVINE scheme consistently outperforms over the existing schemes and provides the promising results.

The massive usage of Internet-of-Things devices in various smart applications enables spectrum scarcity issues. In order to enhance the dynamic spectrum capability, cognitive radio network (CRN) is considered as a key technology to address the spectrum scarcity problem. However, the establishment of a common communication channel in CRN by considering the unlicensed heterogeneous devices in an asynchronous environment is a challenging problem. In this paper, a novel asymmetric asynchronous channel hopping mechanism is designed, where secondary users have different sets of available channels and can enter into the network without any global clock synchronization. The proposed algorithms can guarantee the rendezvous within a small interval of time with minimum inter rendezvous intervals. Simulation results show that the designed protocol outperforms over the existing channel hopping algorithms in terms of the degree of rendezvous, average time to rendezvous and throughput.

Virtual network embedding (VNE) is the process of embedding the set of interconnected virtual machines onto the set of interconnected physical servers (PSs) in the cloud computing environment. The level of complexity of VNE problem increases when a large number of virtual machines with a set of resource demand need to be embedded onto a network of thousands of PSs. The key challenge of VNE is the efficient mapping of virtual networks (VNs), which may have dynamic resource demands. Existing solutions mainly emphasize on the embedding of static VN resulting in poor resource utilization and very low acceptance rate. To tackle such level of complexity in VNE, a fitness-based dynamic virtual network embedding (DYVINE) algorithm is proposed with the goal to maximize the resource utilization by maximizing the acceptance rate. Local and global fitness values of the virtual machines and VN, respectively, are used to utilize the maximum amount of physical resources. The proposed VNE algorithm allows the VN to be dynamic, which indicates that the structure and resource demand can be changed during its execution time. Furthermore, in order to reduce the embedding time in each time slot, a set of PSs is selected to host the VN instead of considering thousands of PSs, which may significantly increase the embedding time. The proposed embedding mechanism is evaluated through extensive simulation and is compared with similar existing embedding algorithms, which outperforms over others.

Irregular spectrum usage and spectrum scarcity in emergency situations is a common problem in industrial wireless networks. To enhance the dynamic spectrum usage, cognitive radio network (CRN) is introduced in various automotive industrial wireless applications named as industrial cognitive radio network (ICRN). However, establishing the control channel by using channel hopping mechanism in ICRN is a challenging problem. In order to achieve reliable performance in ICRN, efficient channel hopping protocols need to be designed. In this paper, two channel hopping protocols are designed for the ICRN with or without the global clock synchronization to maximize the degree of rendezvous within the shortest time, minimize the inter rendezvous intervals and to reduce the maximum time to rendezvous by two secondary users. Performance evaluation of our protocols outperform in terms of throughput, percentage of rendezvous and average time to rendezvous over existing CRN protocols.

Virtualization technology boosts up traditional computing concept to cloud computing by introducing Virtual Machines (VMs) over the Physical Machines (PMs), which enables the cloud service providers to share the limited computing and network resources among multiple users. Virtual resource mapping can be defined as the process of embedding multiple VMs and their network resource demand onto multiple inter-connected PMs. The existing mechanisms of resource mapping need to be efficient enough to minimize the number of PMs without compromising the deadline of the tasks assigned to the VMs, which is NP-hard. To deal with this problem, a Link based Virtual Resource Management (LVRM) algorithm is designed to map the VMs onto PMs based on the available and required resources of the PMs and VMs, respectively. The designed algorithm exploits the fact that the demanded network bandwidth among VMs should be given higher priority while allocating the physical resources to the inter-connected virtual machines as insufficient network bandwidth may detain the task execution. The proposed algorithm is evaluated by a discrete event simulator and is compared with similar virtual network embedded algorithms. Simulation results show that LVRM can outperform over other network embedded algorithms.

Cognitive Radio Network (CRN) is a growing cutting edge technology in the field of wireless communication. The fundamental idea behind CRN is to allow some unlicensed Secondary Users (SUs) who can utilize the spectrum holes in absence of the licensed Primary Users (PUs). Channel Hopping (CH) procedure is followed by the SUs to establish the rendezvous process. In this paper, a novel Asymmetric Synchronous Channel Hopping (ASCH) protocol is proposed in which different SUs can have different sets of channels to establish the rendezvous. Simulation results show that our protocol can achieve better performance over the exiting channel hopping protocols in terms of degree of rendezvous, Maximum Time To Rendezvous (MTTR), and throughput.

In Vehicular Ad Hoc Network (VANET), huge amount of data requests are made by the users from the vehicles traveling through a city. The requested data need to be transmitted and processed by the cloud service providers to maintain the quality of service. In this paper, data transmission time is computed when vehicular data is transmitted to the cloud though the road side units and OpenFlow switches in a Software Defined Network (SDN). The proposed scheme allows some sorts of traffic engineering methods that can be used to address the connectivity problems involving transmission delay and packet loss of the vehicles in a smart city. Simulation results show that the proposed mechanism can achieve better packet delivery rate and least round-trip time as compared to similar data transmission protocols.

Cognitive radio network (CRN) is a promising solution to spectrum scarcity that uses the dynamic spectrum access mechanism to increase the efficiency of the underutilized licensed spectrum. In a CRN, a pair of users exchanges their information at a common unused licensed channel to rendezvous. The rendezvous in all available channels and within the bounded time cycle is a challenging issue in CRNs. In this paper, the primary idea is to construct the channel hopping sequences by using primitive roots of the prime number. For guaranteed rendezvous in CRNs, we design three channel hopping protocols for the symmetric and asymmetric environment in synchronous and asynchronous scenarios of the CRN. Extensive simulation is performed to analyze the throughput, maximum time to rendezvous (MTTR), and average time to rendezvous (ATTR). Simulation results show that our protocols can outperform over the existing protocols and can give significant improvements in terms of MTTR, ATTR, and throughput.

In wireless sensor networks, random deployment of nodes may cause serious coverage overlapping among the nodes and the original network may suffer severe coverage problems due to death of the nodes after deployment. In this paper, efficient distributed coverage hole repair algorithms are proposed taking density of the nodes in the post deployment scenario. The proposed algorithms consider limited mobility of the nodes and can select the mobile nodes based on their degree of coverage overlapping. In order to repair coverage holes of the network, nodes with higher degree of density are moved to maintain uniform network density without increasing the coverage degree of the neighbors of a mobile node. Simulation results show that the energy consumption due to mobility of nodes is least as compared to other similar protocols of the Wireless Sensor Networks. Besides, it is observed that substantial amount of coverage overlapping can be minimized and percentage of coverage of the holes can be maximized.

Bluetooth is a low-cost, low-power and short range communication technology, which operates in 2.4 GHz ISM band. The important research issues in Bluetooth are scatternet formation and routing, since nodes can arrive and depart at arbitrary time. In this paper, novel route maintenance algorithms are proposed for the Bluetooth scatternet that supports mobility of the nodes. Our protocols guarantee the connectivity among nodes and reconstruct the routes dynamically by taking their location information. Besides, we propose how to reduce the number of hops and to form the shortest route between the source and the destination due to addition of nodes. Performance analysis of our work shows that it outperforms in terms of end to end transmission delay, bandwidth consumption and route maintenance as compared to similar Bluetooth routing protocols.

A distributed algorithm for the multihop wireless sensor networks is proposed to construct a novel energy efficient tree topology. The topology is constructed, without taking location information of the sensor nodes and energy conservation of the network is accomplished by controlling the transmission power levels. Experimental results of our protocol show that, total energy consumption of the network is very less as compared to the energy consumption of the network without any power control. Our protocol, being a distributed one, attains the energy conservation up to an optimum level and extends the network lifetime better than the centralized algorithms that we have considered.