An online/offline identity-based short signature (IBSS) protocol permits the signer to produce an online IBSS in real time from a precomputed offline IBSS when given a record. Such techniques are especially valuable in resource-constrained wireless sensor network (WSN) applications. Recently, Meshram et al. presented an UF-IBSS-CMA-protected online/offline IBSS protocol using partial discrete logarithm. In this study, the authors propose an extension of Meshram et al. scheme and compare with other IBSS protocols. The presented offline signing process does not want any private data from the signer. Henceforth, it can be created by any reliable outsider with the private key generation (PKG). This is especially valuable as the base station for a WSN node, performing as a PKG, can produce the offline data and the node does not have to come back to the base station for the re-establishment of the offline data each time signing is implemented. Also, they demonstrate how the scheme can be extended to allow a single user to sign multiple messages and its implementation on WSN.

A central focus of switching theory is on non-blocking properties of switches and their scalability. Several types of conditionally non-blocking switches have been known to be preserved by the two-stage interconnection network. The preservation of each type is by a separate theory. This study presents a coherent theory that yields an infinite family of preserved types, incorporating all known ones. Recursive two-stage interconnection networks, including all banyan-type networks, construct conditionally non-blocking switches that are most compact in connecting every input to every output and rich in applications.

In the mobile environment, the movement of users, disconnected modes, many data updates, power battery consumption, limited cache size, and limited bandwidth impose significant challenges to information access. Caching is considered one of the most important concepts to deal with these challenges. There are two general topics related to the client cache policy: cache invalidation method keeps data in the cache up to date; and cache replacement method chooses the cached item(s) which should be deleted from the cache when the cache is full. The aim of this work is to propose a new technique for cache replacement in a mobile database that takes into consideration the impact of invalidation time for enhancing data availability in the mobile environment by using genetic programming. In this case, each client collects information for every cached item in the cache like access probability, cached document size, validation time and uses these factors in a fitness function to determine cached items that will be removed from the cache. The experiments were performed using Network Simulator 2 to evaluate the effectiveness of the proposed approach, and the results are compared with the existing cache replacement algorithms. It is concluded that the proposed approach performs significantly better than other approaches.

This study deals with the impact of unlicensed Internet of Things (IoT) network coexistence in terms of packet collision. The classical packet collision studies based on the Poisson distributed process generally assume homogeneous networks with packets of equal lengths. The authors propose a new approach which can be applied to a more general context including heterogeneous networks and different packet lengths. The proposed approach is based on modelling the vulnerable period and the packet length as uniform random variables. Then, the two main IoT networks considered in unlicensed spectrum, LoRa and Sigfox, are being investigated in more detail. For these two networks, closed-form analytical formulas for the intra-and inter-network probability of packet collisions between nodes are provided and confirmed by simulations results. For this context, it is also shown that the ultra-narrow band feature of Sigfox is rather a drawback than an advantage from the collision point of view. To enhance the probability of collision, some possible evolutions of the Sigfox physical layer are finally suggested.

In machine-to-machine (M2M) networks, the ability to access the radio channel requires a rigid design of a medium access control (MAC) protocol. Here, an optimised hybrid MAC protocol will be proposed which is composed of two main processes, the contending process and the transmission process. During contention process, the devices randomly contend the transmission opportunities with equal probabilities by using the conventional-based slotted ALOHA (S-ALOHA) mechanism. Only successful devices can assign a transmission slot during the transmission process by using the reservation-based time division multiple access mechanism. Additionally, an optimisation problem will be formulated to obtain the maximum aggregated throughput. Moreover, the optimum relation between the contention and transmission periods under different number of devices is calculated. The optimisation problem is solved with the aid of mathematical analysis which is carried out through Monte Carlo simulation. Furthermore, extensive MATLAB programs are executed to study the system performance in terms of: the system throughput, the average packet delay, the success access ratio, and the reservation ratio. The simulation results show that the proposed hybrid technique outperforms other related hybrid when compared.

Energy efficiency (EE) is considered as one of the pivotal uplink (UL) performance metrics for 5G dense networks. It consists of two conflicting objectives that are recognised as benefit–cost ratio: spectral efficiency and energy consumption. Accordingly, network design tradeoff is the key challenge for future networks. In this paper, we aim to jointly maximise network spectral efficiency and minimise power consumption with respect to the following design parameters: base station (BS) density, users' number, equipped antennas' number, and signal-to-noise power ratio without losing service quality. The performance of the ultra-dense network is characterised on the basis of the Pareto optimality concept through the following benchmarks: (i) studying impact of exhausted power on the deployed hardware elements. (ii) Validating the total EE performance through Monte-Carlo simulation within a low cost of processing time. (iii) The proposed approach is compared against single objective scheme to show the significance of the design tradeoff. Furthermore, we will introduce a detailed mathematical analysis for UL power policy and channel estimation for reliable pilot reusing. Simulation results will show that our proposed solution guarantee remarkable EE performance via reducing the number of deployed BSs without scarificing service quality.

GridSim is a widely used grid simulation tool. Since it simulates a grid environment well, it has been widely used in studies of grids. Many researchers have proposed various load-balancing techniques in the grid, but all those cannot be used in GridSim due to the structural differences of the grid. In this study, the authors propose an enhanced load balancing method called enhanced GridSim with heterogeneity aware load balancing (EGHLB) for GridSim. The proposed algorithm EGHLB estimates system parameters such as load on the resource, the expected finish time of a Gridlet on resources on each Gridlet arrival and then balances the load by providing a new mechanism of scheduling which prevents the resource overloading and executes all the Gridlets on the heterogeneous resources within the assigned deadline. A selection method for efficient scheduling of Gridlets among heterogeneous resources is presented by taking into account the deadline, network heterogeneity, and resource heterogeneity. They simulate the proposed algorithm on the GridSim platform.

The target coverage optimisation is an important problem in directional sensor networks (DSNs). In this study, the authors present a novel algorithm, called cover critical target first (CCTF), for improving the coverage ratio in DSN. CCTF simultaneously maximises the number of covered targets, reduces the number of active sensors, and extends network lifetime. For a set of uncovered targets, CCTF always finds the highest priority target which has the minimum number of covering sensors. Among sensors that could cover this target, CCTF activates a sensor that covers more additional targets besides the found target. CCTF's performance is evaluated in terms of coverage ratio, the number of active sensors, and power consumption through extensive simulation. The simulation indicates that CCTF is robust against orientation and localisation errors.

Energy efficiency is a major factor in designing wireless sensor networks (WSNs). Clustering design and grid-based scheme are one of the techniques to save energy in WSNs. However, for a mobile sink in WSNs, packet loss rate that occurs due to the sink mobility is also a significant challenge. Here, an enhanced routing-G _i protocol for a mobile sink in WSNs has been proposed to not only enhance energy efficiency but also minimise the packet loss rate. Simulation results show that the proposed protocol is more efficient than the previous protocols in terms of the network lifespan, energy efficiency, and packet delivery ratio. Thus, the proposed approach in this work could further be adapted to investigate highly mobility of sink in WSNs.

Ack-storm DoS attacks are injection attacks against an active Transmission Control Protocol (TCP) connection. These attacks can be generated by a very weak adversary and can generate amplification factor of orders of magnitude by exploiting a weakness in the TCP protocol specification. This attack requires sending two packets by the adversary with acknowledgement number greater than the sequence number used in each direction and the two end hosts will attempt to re-synchronise the sequence numbers by sending duplicate acknowledgement and enter a loop. In this study, the authors propose a state transition model based detection scheme to detect these DoS attacks. This state transition machine called constrained counting automata (CCA) has the ability to count the number of times a state has been revisited and its transitions are constrained by invariant conditions to be satisfied. They model the chances of receiving a packet with acknowledgement number greater than the sequence number used by its peer as a probability distribution and use it to set appropriate value of threshold on revisits of a state for detecting attack. By experimenting within a local network and in Internet, they show that CCA can detect Ack-storm DoS attacks.

Spectrum trading has been permitted in most of the major wireless markets to facilitate better utilisation of spectrum. The authors have considered a spectrum trading framework in which a wireless service provider (WSP) leases its available channel(s) to another WSP for use at the designated base station (BS) of the latter for short duration. In their model, the agents of WSPs carry out the negotiation on the specifications of the channel usage such as transmission power, antenna height, spectrum band of the channel and price of the channel. In this work, they have modelled the negotiation as a multi-issue bilateral negotiation problem. Initially, they have solved the problem with the help of the Bayesian learning-based negotiation (BLBN) method. Furthermore, they have devised the novel reinforcement learning-based technique namely, reinforcement learning-based negotiation (RLBN) considering the adaptability of the BS to the new channel configuration. Surplus utility and convergence time of the negotiation process are considered as performance indices for the above techniques. The simulation results show that the RLBN outperforms BLBN and static negotiation technique as far as the objective of surplus utility is concerned.

Sensors with IoT assistance provides secured communication and data integrity inside HAN. Energy reading and information flow from the smart grid, together with sensors, bring about a new perspective on energy management. This paper primarily investigates the secured data flow in HAN and assures data privacy of customers during critical and emergency operations. Data are made available in real time with minimum transit time delay. Devices are continuously monitored for vital and emergency services. This paper focuses on machine to machine data flow and packet delivery using IoT. It helps in making user's power consumption data available over the cloud and also in customised electronic devices in real-time. This research work showcases the requirements for developing a cost-effective IoT-HAN connected with smart grid for energy aware routing. The advanced design scheme helps to place sensors, and control gateway in a well-defined boundary, consuming less energy for data transfer and data processing. Data flow pattern and packet delivery rate is tested using both simulated and actual data from sensors and concentrators. The obtained results and flow pattern is evaluated using MATLAB and network simulator. The developed IoT-HAN setup is optimally helpful in secured data exchange among different connected devices inside HAN.

Software-defined networking (SDN) is a new paradigm that allows developing more flexible network applications. A SDN controller, which represents a centralised controlling point, is responsible for running various network applications as well as maintaining different network services and functionalities. Choosing an efficient intrusion detection system helps in reducing the overhead of the running controller and creates a more secure network. In this study, we investigate the performance of the well-known anomaly-based intrusion detection approaches in terms of accuracy, false alarm rate, precision, recall, f1-measure, area under receiver operator characteristic curve, execution time and McNemar's test. Precisely, the authors focus on supervised machine-learning approaches where we use the following classifiers: decision trees, extreme learning machine, Naive Bayes, linear discriminant analysis, neural networks, support vector machines, random forest, K-nearest-neighbour, AdaBoost, RUSBoost, LogitBoost and BaggingTrees where we employ the well-known NSL-KDD benchmark dataset to compare the performance of each one of these classifiers.

To achieve greater performance in computing networks, a setup of critical computing aspects that ensures efficient network operation needs to be implemented. One of these computing aspects is quality of service (QoS). QoS capable of networking allows efficient control of traffic, especially for network critical data. However, to achieve this in wireless sensor networks (WSNs) is a serious challenge, since these technologies have computing limitations. It is even difficult to manage networking resources with ease in these types of technologies, due to their communication, processing and memory limitations. Even though this is the case with WSNs, they have been largely used in monitoring/detection systems, and by this proving their application importance. In this study, a resource-aware OpenFlow-based active network management QoS scheme that uses software defined networking (SDN) strategies is proposed and implemented to apply QoS requirements for managing traffic congestion in WSNs. This scheme uses SDN programmability strategies to apply network QoS requirements and perform traffic load balancing to ensure congestion control in software defined WSNs. The experimental results show that the developed scheme is able to provide congestion avoidance within the network. It also allows opportunities to implement flexible QoS requirements based on the system's traffic state.

With technological advancements, vehicles are equipped with abundant storage capability and powerful computing capability. This leads to an advanced kind of vehicular ad hoc network service, which enables local collaborations among vehicles to produce service data an individual cannot make alone. To support this advanced service, a vehicular cloud (VC) is proposed. One VC usually adopts flooding to acquire data, so the data acquisition cost is relatively high. To reduce the cost, the authors employ the address-based unicast to achieve data acquisition and propose a data acquisition method based on address-based VC. In this method, the unicast address and data address are proposed to establish a relationship between one kind of specific data and an address. On the basis of the data address, a vehicle can retrieve data from the nearest VC member in the unicast way, so the data acquisition cost is reduced. This proposal is evaluated, and the data show that the data acquisition cost is effectively reduced.