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The evolution of wireless networks towards high mobility has led to the concept of connecting vehicles. Wireless link quality is a vital attribute of a dynamic vehicular environment and a backbone ...

Background: With the availability of multiple options in wireless network simultaneously, Always Best Connected (ABC) requires dynamic selection of the best network and access technologies. Objective: In this paper, a novel dynamic access network selection algorithm based on the real time is proposed. The Available BandWidth (ABW) of each network is required to be estimated to solve the network selection problem. Methods: Proposed algorithm estimates available bandwidth by taking averages, peaks, low points and bootstrap approximation for network selection. It monitors real-time internet connection and resolves the selection issue in internet connection. The proposed algorithm is capable of adapting to prevailing network conditions in heterogeneous environment of 2G, 3G and WLAN networks without user intervention. It is implemented in temporal and spatial domains to check its robustness. Estimation error, overhead, estimation time with the varying size of traffic and reliability are used as the performance metrics. Results: Through numerical results, it is shown that the proposed algorithm’s ABW estimation based on bootstrap approximation gives improved performance in terms of estimation error (less than 20%), overhead (varies from 0.03% to 83%) and reliability (approx. 99%) with respect to existing techniques. Conclusion: Our proposed methodology of network selection criterion estimates the available bandwidth by taking averages, peaks, and low points and bootstrap approximation method (standard deviation) for the selection of network in the wireless heterogeneous environment. It monitors realtime internet connection and resolves internet connections selection issue. All the real-time usage and test results demonstrate the productivity and adequacy of available bandwidth estimation with bootstrap approximation as a practical solution for consistent correspondence among heterogeneous wireless networks by precise network selection for multimedia services.

Wireless communication-based services compromised with security threats due to the open channel communication model. Free communication channel models have limited bandwidth and open port communica...

The telecommunication industry has changed the way we communicate, work and socialize in a remarkable way since its inception. This change is continuous as new services and applications are being d...

The elliptic curve cryptography (ECC) has been a promising alternative to RSA algorithm particularly for resource constrained environment like Internet of things. Efficient implementation of ECC for low power applications has been a challenging task in wireless technologies. Computability and complexity of the realization process of ECC are the major performance parameters. In this paper, we present software implementation of ECC utilizing the Weierstrass curve. It offers insights on the implementation process and helps in identifying the important operations used for the ECC. Following the hierarchy of the operations and aiming to optimize the important operations including scalar multiplications and inversions, it presents an in-depth study toward achieving enhanced execution efficacy of the ECC.

In the era of big data, Wireless Multimedia Sensor Networks (WMSNs) have emerged as an enabling and effective technology for multimedia data sensing in physical environment. Wireless communication being resource constrained finds it difficult to support the volume and the type of big data traffic for acquisition and distribution. It poses complex technical challenges particularly in terms of computational power, transmission bandwidth, and energy consumption. In this paper, we have presented an account of important features and requirements of WMSNs for monitoring and analyzing the data recorded through multimodal sensors. Recent fusion strategies including those based on artificial intelligence for achieving improved accuracy in extracting the intelligence from big data are analyzed. Their limitations are identified and probable solutions in context with the real-field deployment of the emerging ubiquitous computing systems are outlined.

Numerous wireless communication technologies have been employed to manage mobile users anywhere, any time and anyhow. Additionally, users are more and more fascinated by multimedia applications such as voice, audio and video, which require Quality of Service (QoS) support. To retain the user with Always Best Connected network in such restrictions is a challenging issue. A contemporary approach for efficient network selection in wireless heterogeneous networks is conferred. The approach composed of two criteria: the first is the cost function comprising of received signal strength, available bit rate, signal to noise ratio, throughput and bit error rate metrics. The metrics’ respective weights are being optimized by Particle Swarm Optimization (PSO). The second criterion consists of fuzzy logic system fed with similar metrics as inputs and targeted towards same output. The final decision of network selection is taken by the blend of these two criteria. Simulation results indicated that the proposed scheme based on Cost function, PSO and Fuzzy system (C-P-F) provided better performance in terms of minimizing the unnecessary handoffs (network selection rate), utility degree and load balancing. The proposed algorithm (C-P-F) significantly reduces the network selection rate by 50% as compared to existing algorithm based on cost function and PSO. This reduction indicated higher probability of guaranteed session continuity and good quality of the currently running service, which resulted in high user satisfaction levels. It enhances user satisfaction 55% and reduced network selection rate upto 75% in comparison of existing network selection techniques.

With rapid development in wireless communication, Intelligent Transportations System (ITS) has received significant attention. This system delivers various social and economic benefits including efficient traffic management, lesser prone to accidents, reduced air pollution and enabling of unmanned driving for enhanced leisure. ITS is enabled through real-time communication either Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) modes of intra-infrastructure communication. LTE-V2V is seen as a major technology towards ITS implementation. In this paper, we discuss various autonomous resource selection techniques available for Mode-4 V2V communication under LTE-A network. An enhanced resource selection scheme based on exponential averaging in time domain and normalized scaling in frequency domain is being proposed. Simulation results show the efficacy of the proposed algorithm in terms of packet reception ratio (PRR), error rate and update delay. The proposed scheme enables low latency transmission of cooperative awareness messages while maintaining high PRR and low error rate.

Platooning is one of the key applications of Intelligent Transportation System (ITS) for the smart cities. Various wireless technologies have been proposed for meeting the stringent requirements of platooning. 3GPP has initiated standardization work for LTE based V2V communication. It offers potential means to support transmission of safety critical messages among platoon vehicles with high reliability, security and ultra low latency. However, efficient resource allocation has been a challenge in LTE based networks. In this paper, we propose a Cooperative-Reinforcement Learning (C-RL) based resource selection algorithm for communication among connected vehicles utilizing LTE-Direct technology. The proposal outperforms the distributed resource selection scheme in terms of actual time required for Cooperative Awareness Messages (CAM) dissemination among vehicles forming the platoon and performance of other vehicular links sharing the similar Resource Blocks (RBs). Simulation results shows the efficacy of the proposed algorithm in terms of efficient resource utilization and faster dissemination of messages among the connected vehicles.

The Internet of Things is a paradigm that involves physical objects with capabilities of sensing, information processing and communication through wireless or wired connection. These physical objects having embedded intelligence and hence decision-making capabilities act as smart things. The paradigm of IoT embraces various domains including sensors, information and communication technology, memory space, data analytics, machine learning and security and privacy mechanisms. The ‘things’ are constrained in terms of computing power, memory space and data rate and hence need innovative approaches to address the technical challenges present in the real-life implementation of the concept. This work presents a brief introduction to IoT concept, representative discussion on constituent domains and highlights of the technical challenges therein open for research community.

Internet of Things (IoT) is a technology to create smart world. To enable an IoT system, communication plays an important role. Everything in IoT depends on the flow of information. Many wireless technologies are available for the purpose but the choice for the right technology depends on the use case requirements. Reliability and availability of an IoT application is the outcome of reliable communication. Issues like scalability and heterogeneity present numerous challenges to the researchers. Mobility maintenance, packet delay, signal load, etc., are challenges that make reliable communication difficult and affect the quality of service. This paper presents the details of wireless technologies available for the IoT and discusses the open challenges and research issues in IoT.

One of the important aspects of seamless communication for ubiquitous computing is the dynamic selection of the best access network for a multimodal device in a heterogeneous wireless environment. In this paper, we consider available bandwidth as a dynamic parameter to select the network in heterogeneous environments. A bootstrap approximation based technique is firstly utilized to estimate the available bandwidth and compare it with hidden Markov model based estimation to check its accuracy. It is then used for the selection of the best suitable network in the heterogeneous environment consisting of 2G and 3G standards based wireless networks. The proposed algorithm is implemented in temporal and spatial domains to check its robustness. The numerical results show that the proposed algorithm gives improved performance in terms of estimation error (less than 15%), overhead (varies from 0.45% to 72.91%) and reliability (approx. 99%)as compared to the existing algorithm.

Cognitive radio is a new paradigm in wireless communication for improving the spectrum utilization. Spectrum sensing is a fundamental component of cognitive radio networks. Among all the available spectrum sensing algorithms, energy detection scheme has gained more interest owing to its simple implementation. In this paper, we propose a threshold setting algorithm for energy detection scheme which aims at maximizing the spectrum utilization. A closed-form expression for adaptive threshold for maximal spectrum utilization is derived and analyzed. Numerical results demonstrate that the proposed scheme outperforms the conventional methods of determining the threshold.

Multi radio, multi hop, self organizing and self configuring wireless technology are the characteristic features of wireless mesh networks (WMNs) to offer last mile access to end users. The emergence of stochastically varying network environments critically affects routing in WMNs. Any routing policy meant for WMNs must be quickly adaptive and evolve in a decentralized self organizing and self configuring manner. This paper firstly proposes formulation of a soft computing i.e. fuzzy logic based hybrid performance metric which includes per flow (throughput, delay and jitter) as well as per node (residual energy of the node) parameters. This fuzzy logic based hybrid performance metric enumerates the integrated link cost (ILC) which is used as distance measure between two adjacent nodes. The paper further proposes three routing algorithms based upon nature inspired computing approaches namely firefly algorithm, Big Bang Big Crunch and Ant Colony Optimization. The proposed routing approaches aim at finding the minimal ILC path within a stipulated time constraint. The time constraint is governed by the mobility of network nodes. Extensive simulations were conducted for various WMN topologies. The results of the proposed approaches have been compared with two commonly used conventional approaches and were found to be far more superior. It was also observed that the self organizing capability of the proposed nature inspired routing approaches effectively reduces the complexity and makes a network quite adaptive to the dynamic network behavior found in WMNs.

In wireless communication, new radio access technologies are emerging, capable of supporting larger coverage area and faster data rates. In a wireless heterogeneous environment consisting of disparate radio access technologies, selection of the best network is an important research issue. In this paper, we propose a novel network selection algorithm for a heterogeneous environment consisting of WiMAX and LTE standard. The proposed algorithm is based on received signal strength, signal to noise ratio, available bit rate, achievable throughput and bit error rate. Relative weights of the decision making attributes are optimized by employing particle swarm optimization approach. The number of satisfied users calculated (as per their demand with wireless network selected) by proposed algorithm is optimized by modified PSO and confirmed by Monte Carlo method. From the simulation results it is inferred that the number satisfied users while running multimedia applications has been improved by 50 % as compared to the existing network selection algorithms.

Network selection in a heterogeneous wireless environment is a major challenge to ensue seamless mobility across different radio air interfaces. To provide the desired quality of service for a given application in a multimedia environment, different parameters, including delay, bandwidth, packet loss and cost per byte, play an important role in network selection. In this paper, we present a novel algorithm for optimal network selection. A heterogeneous environment consisting of four networks, UMTS, WLAN, GPRS and WiMAX has been considered. We propose a network selection algorithm in which weight estimation for the representative set of the network attributes is computed using entropy and technique for order preference by similarity to ideal solution approach. The numerical results show that the proposed model can be effectively implemented to select the desired network in a heterogeneous environment employing triple-play services.

Deployment of heterogeneous wireless networks is spreading throughout the world as users want to be connected anytime, anywhere, and anyhow. Meanwhile, users are increasingly interested in multimedia applications such as audio, video streaming and Voice over IP (VoIP), which require strict Quality of Service (QoS) support. Provisioning of Always Best Connected (ABC) network with such constraints is a challenging task. Considering the availability of various access technologies, it is difficult for a network operator to find reliable criteria to select the best network that ensures user satisfaction while reducing multiple network selection. Designing an efficient Network selection algorithm, in this type of environment, is an important research problem. In this paper, we propose a novel network selection algorithm utilizing signal strength, available bit rate, signal to noise ratio, achievable throughput, bit error rate and outage probability metrics as criteria for network selection. The selection metrics are combined with PSO for relative dynamic weight optimization. The proposed algorithm is implemented in a typical heterogeneous environment of EDGE (2.5G) and UMTS (3G). Switching rate of the user between available networks has been used as the performance metric. Moreover, a utility function is used to maintain desired QoS during transition between networks, which is measured in terms of the throughput. It is shown here that PSO based approach yields optimal network selection in heterogeneous wireless environment.

Always best connected services (ABC) allow multimode mobile terminals to stay connected to the best available networks, at anytime according to user preferences. One of the key aspects in realizing such ABC service is mainly attributed to an effective and dynamic access network selection process. However, most of the previous works consider the access network selection process as a static optimization problem which fails to address the dynamic QoS conditions intrinsic in wireless networks. One of the main challenges remaining is to find an efficient way of obtaining dynamic QoS parameters such as available bandwidth. In this paper, propose a novel dynamic access network selection algorithm capable of adapting to prevailing network conditions. Proposed algorithm is an estimation process where network selection in heterogeneous wireless environment (WiMAX & WLAN) performed using available bandwidth estimation relies on dynamic parameters designed using .net.

4G wireless networks are based on All-IP architecture integrating cellular networks, Wireless local area networks, Worldwide Interoperability for Microwave Access, Wireless ad hoc networks, and Wireless Personal Area Networks etc. This makes seamless handover an important issue for users roaming among these networks. Anticipation of future events based on layer 2 (L2) trigger information is the basic principle of fast handover. It incurs higher signaling costs compared with the other protocols like Mobile IPv6 and Hierarchical Mobile IPv6. L2 trigger is based on fluctuating wireless channel states. Therefore, the handover anticipation using L2 trigger may sometimes be incorrect. Unnecessary buffer space is used for providing a smooth handover in the case of incorrect anticipation. Therefore, it is very important to analyze overhead costs and compare the performance of IP based handover protocols. This paper investigates the impact of L2 triggering time on the signaling cost, packet delivery cost, total overhead cost, and buffer space. Results show that Session to mobility ratio, L2 trigger time and number of subnets are determining parameters for optimizing handover performance.

Fourth Generation (4G) Wireless System will integrate heterogeneous wireless overlay systems i.e. interworking of WLAN/ GSM/ CDMA/ WiMAX/ LTE/ etc with guaranteed Quality of Service (QoS) and Experience (QoE).QoS(E) vary from network to network and is application sensitive. User needs an optimal mobility solution while roaming in Overlaid wireless environment i.e. user could seamlessly transfer his session/ call to a best available network bearing guaranteed Quality of Experience. And If this Seamless transfer of session is executed between two networks having different access standards then it is called Vertical Handover (VHO). Contemporary VHO decision algorithms are based on generic QoS metrics viz. SNR, bandwidth, jitter, BER and delay. In this paper, Error Vector Magnitude (EVM) is proposed to be a generic QoS trigger for VHO execution. EVM is defined as the deviation of inphase/ quadrature (I/Q) values from ideal signal states and thus provides a measure of signal quality. In 4G Interoperable environment, OFDM is the leading Modulation scheme (more prone to multi-path fading). EVM (modulation error) properly characterises the wireless link/ channel for accurate VHO decision. EVM depends on the inherent transmission impairments viz. frequency offset, phase noise, non-linear-impairment, skewness etc. for a given wireless link. Paper provides an insight to the analytical aspect of EVM & measures EVM (%) for key management subframes like association/re-association/disassociation/ probe request/response frames. EVM relation is explored for different possible NAV-Network Allocation Vectors (frame duration). Finally EVM is compared with SNR, BER and investigation concludes EVM as a promising QoS trigger for OFDM based emerging wireless standards., 12 pages, 7 figures, IJWMN 2010 august issue vol. 2, no.3

Mobility management is the most important feature of a wireless cellular communication system. Continuation of an active call is one of the most important quality measurements in the cellular systems. Handover makes it possible for a user to travel between various networks or cells while having a seamless connection. This paper shows that, performance of cellular network can be increased with proposed adaptive soft handoff algorithm, which dynamically calculates the Soft handover margin based on the received signal strength and distance. Performance is evaluated in terms of the performance metrics active set update rate, active set size, soft handover region and probability of outage. Simulation results show that soft handover algorithm gives better performance with adaptive soft handoff margin compared to that of fixed soft handover margin in varied propagation conditions.

Main focus of our study here is how to reach optimum compression in the wireless Multimedia Sensor Network (WMSN) so as to improve power allocation between compression and transmission for maximizing the battery life of sensors. We know that there exists a large redundancy in sensor's data. So data need to be compressed before being transmitted to the sink/receiver/customer for reducing the heavy amount of energy consumed in transmission, but wireless sensor are very limited to computational ability, memory and energy. Due to these limitations, it becomes a sincere issue while processing any compression algorithm on the data because this also requires a significant amount of energy to perform these operations but even so, for a single bit, the energy used for compression is usually less than that of transmission. But if algorithm is highly complex and requires execution of a very large number of operations then the high degree of compression may also consume more energy than that of transmission. Here we can clearly see that there must be balance between power consumption of data transmission and that of compression. The power of compression depends on many factors such as amount of data to be reduced, compression algorithm, compression ratio, processor's architecture, etc. Our scheme is primarily focused on the video sensor networks which optimizes the balance between compression and transmission; and consequently, the overall power consumption will be reduced. In our results, we have discussed the variation of optimum compression ratio with respect to various model parameters and shown the power consumption behaviour for a typical model and achieved the minimum power consumption on optimum value of compression.

In this paper, we analyze the behavior of inter-system handover between second generation (GSM) and third generation (UMTS) mobile radio systems. A mathematical model is proposed to evaluate the handover performance. The handover initiation algorithm is based on the absolute signal strength thresholds. The algorithm performs handover when the averaged signal strength from the serving base station drops below a given threshold and that from the candidate base station exceeds a preset threshold. Handover rate and handover initiation delay are used as performance metrics. Based on numerical results, threshold parameter settings are determined for optimum handover performance.

Cognitive Radio is a new paradigm in wireless communication to tackle the problem of spectrum underutilization. One of the important functions of cognitive radio is spectrum sensing. There are many spectrum sensing algorithms available in the literature out of which energy detection is widely used because it is easy to implement and it does not require prior information about PU (Primary User). However, the performance of the conventional energy detector deteriorates in low SNR region. Double threshold CSS (Cooperative Spectrum Sensing) was introduced to increase the reliability of decision but at the cost of some sensing information lost. In this paper, we are discussing a method of double threshold CSS in which each CR (Cognitive Radio) sends local decision or observed energy to the FC (Fusion Center) depending on the region in which the observed energy lies. FC then makes a final decision by combining local decisions and observed energy values. We have developed a simulation model to prove the superiority of the proposed algorithm and it has been observed that the proposed method outperforms the conventional CSS in low SNR region. There is almost a 10% improvement in the cooperative probability of detection at −8 dB SNR at 0.1 probability of false alarm.

Future Heterogeneous wireless network (HetNet) will foster cognitive Vertical Handover (VHO) to exploit the ubiquitous diversity which is defined as seamless transfer of a session between different Radio Access Technologies (RATs). Classical VHO mechanisms lacks to expedite the effect of spectrum sensing for network selection which greatly affects the Quality of Experience (QoE) of both Access Node (AN) and Mobile Node (MN). Therefore, Paper proposes Error Vector Magnitude (EVM), which measures error in modulation quality and characterizes neighboring ANs. To maximize the overall network resource utility, EVM based multi-tenderee bidding model is proposed which utilises cooperative game theory. Performance is compared with classical MADM bidding model in terms of network bid value and total HetNet payoff. Results show that EVM based bidding increases the payoff by ∼ 49.3 % when compared with classical MADM bidding model.

Cognitive radio is the key technology for future wireless communication. Spectrum sensing is one of the most important functions in cognitive radio (CR) applications. It involves the detection of primary user (PU) transmissions on a preassigned frequency band. PU licensed band can be sensed via appropriate spectrum sensing techniques. In this paper, we consider three basic spectrum sensing techniques of transmitter detection: Matched filter detection, Energy detection, and Cyclostationary feature detection. Using simulations, a comparative analysis of the three techniques has been carried out in terms of probability of false alarm Pf, probability of detection alarm Pd, and probability of miss detection Pm. Finally, Numerical result shows that at low signal to noise ratio (SNR), cyclostationary feature detection outperforms other two techniques, thus have some difficulties like implementation is complex, long observation time, etc. For simulation we used MATLAB software.

In soft handover process, the mobile station maintains simultaneous communication with multiple base stations near the cell boundary. This increases overhead on the radio and network resource utilization. Proper design of handover, therefore, becomes a challenging task for radio resource management in 3G wireless mobile networks. In this paper, we analyze the performance of soft handover algorithm based on pilot signal strength measurements. Outage probability is used as the performance metric. The impact of averaging window size and time to trigger on the outage probability is presented. Finally, based on the numerical results obtained via simulation, proper settings of averaging window size and time to trigger are determined for optimized handover performance for the given system parameters.