Showing papers in "Wireless Personal Communications in 2017"

Software-Defined Fog Network Architecture for IoT

Abstract: Rapid increase in number and diversity of Internet-connected devices raises many challenges for the traditional network architecture, which is not designed to support a high level of scalability, real-time data delivery and mobility. To address these issues, in this paper we present a new model of Internet of Things architecture which combines benefits of two emerging technologies: software-defined networking and Fog computing. Software-defined networking implies a logically centralized network control plane, which allows implementation of sophisticated mechanisms for traffic control and resource management. On the other hand, Fog computing enables some data to be analysed and managed at the network edge, thus providing support for applications that require very low and predictable latency. In the paper, we give detailed insight into the system structure and functionality of its main components. We also discuss the benefits of the proposed architecture and its potential services.

Genetic Algorithm Based Demand Side Management for Smart Grid

Abstract: Electricity usage at electricity rush hour (peak hour) may vary from each and every service area such as industrial area, commercial area and residential area. Equalizing the power consumption in industry may lead to the utilization of power in other service areas in an efficient way. Although industries have comparably lesser number of power consuming device types than other service areas the power consumption is quite high. To meet the demands rising in the industry, shiftable loads (devices) can be redistributed equally to all the working time slots based on the average power utilization. It can be done in a flexible manner by shaping the loads using Demand Side Management (DSM) technique in Smart Grid. The main objective is to minimize the power utilization during the electricity rush hour by effectively distributing the power available during off-peak hour. Evolutionary algorithm can be well adapted to problems where optimization is the core criteria. Any maximization or minimization problem can be solved efficiently using evolutionary algorithm. Hence, to obtain the optimized fitness function of load redistribution in industry Genetic Algorithm in Demand Side Management (GA-DSM) is chosen and it has benefited with an overall reduction of 21.91% which is very remarkable. In addition to this the evaluation of the fitness function using GA-DSM is carried out in other two industrial dataset models (steel plant and wind power plant) which is unavailable so far in the literature.

Data Aggregation in Wireless Sensor Networks: Previous Research, Current Status and Future Directions

Abstract: Wireless sensor networks (WSNs) consist of large number of small sized sensor nodes, whose main task is to sense the desired phenomena in a particular region of interest. These networks have large number of applications such as habitat monitoring, disaster management, security and military etc. Sensor nodes are very small in size and have limited processing capability as these nodes have very low battery power. WSNs are also prone to failure, due to low battery power constraint. Data aggregation is an energy efficient technique in WSNs. Due to high node density in sensor networks same data is sensed by many nodes, which results in redundancy. This redundancy can be eliminated by using data aggregation approach while routing packets from source nodes to base station. Researchers still face trouble to select an efficient and appropriate data aggregation technique from the existing literature of WSNs. This research work depicts a broad methodical literature analysis of data aggregation in the area of WSNs in specific. In this survey, standard methodical literature analysis technique is used based on a complete collection of 123 research papers out of large collection of 932 research papers published in 20 foremost workshops, symposiums, conferences and 17 prominent journals. The current status of data aggregation in WSNs is distributed into various categories. Methodical analysis of data aggregation in WSNs is presented which includes techniques, tools, methodology and challenges in data aggregation. The literature covered fifteen types of data aggregation techniques in WSNs. Detailed analysis of this research work will help researchers to find the important characteristics of data aggregation techniques and will also help to select the most suitable technique for data aggregation. Research issues and future research directions have also been suggested in this research literature.

The IoT Architectural Framework, Design Issues and Application Domains

Abstract: The challenge raised by the introduction of Internet of Things (IoT) concept will permanently shape the networking and communications landscape and will therefore have a significant social impact. The ongoing IoT research activities are directed towards the definition and design of open architectures and standards, but there are still many issues requiring a global consensus before the final deployment. The paper presents and discusses the IoT architectural frameworks proposed under the ongoing standardization efforts, design issues in terms of IoT hardware and software components, as well as the IoT application domain representatives, such as smart cities, healthcare, agriculture, and nano-scale applications (addressed within the concept of Internet of Nano-Things). In order to obtain the performances related to recently proposed protocols for emerging Industrial Internet of Things applications, the preliminary results for Message Queuing Telemetry Transport and Time-Slotted Channel Hopping protocols are provided. The testing was performed on OpenMote hardware platform and two IoT operating systems: Contiki and OpenWSN.

Deployment Strategies in the Wireless Sensor Networks: Systematic Literature Review, Classification, and Current Trends

Abstract: Wireless sensor network (WSN) is one of the interesting issues in the information technology domain. It is used in various fields such as medicine, agriculture, meteorology, etc. that eases lots of difficult tasks to do but have some challenges too. Deployment is the greatest challenge in WSN that affects other features like coverage, connectivity, energy efficient and lifetime. Despite the importance of the deployment problem in WSN, to the best of our knowledge, there isn't any systematic literature review to give us systematical analyses the state-of-the mechanisms in this field. Therefore, this study reviewed the deployment mechanisms which have been used in WSN systematically. The deployment mechanisms can be classified into two main categories: deterministic and nondeterministic. Also, this study represents a comparison of the important techniques of the selected articles in each category to offer a guideline for further studies and new challenges. We also have noted some open issues for future research.

Precise Indoor Positioning Using UWB: A Review of Methods, Algorithms and Implementations

Abstract: The demand and growth of indoor positioning has increased rapidly in the past few years for a diverse range of applications. Various innovative techniques and technologies have been introduced but precise and reliable indoor positioning still remains a challenging task due to dependence on a large number of factors and limitations of the technologies. Positioning technologies based on radio frequency (RF) have many advantages over the technologies utilizing ultrasonic, optical and infrared devices. Both narrowband and wideband RF systems have been implemented for short range indoor positioning/real-time locating systems. Ultra wideband (UWB) technology has emerged as a viable candidate for precise indoor positioning due its unique characteristics. This article presents a comparison of UWB and narrowband RF technologies in terms of modulation, throughput, transmission time, energy efficiency, multipath resolving capability and interference. Secondly, methods for measurement of the positioning parameters are discussed based on a generalized measurement model and, in addition, widely used position estimation algorithms are surveyed. Finally, the article provides practical UWB positioning systems and state-of-the-art implementations. We believe that the review presented in this article provides a structured overview and comparison of the positioning methods, algorithms and implementations in the field of precise UWB indoor positioning, and will be helpful for practitioners as well as for researchers to keep abreast of the recent developments in the field.

Micro operators to boost local service delivery in 5G

Abstract: Future digital society depends heavily on timely availability of high quality wireless connectivity the offering of which today is dominated by mobile network operators (MNOs). Future 5G systems aim at connecting billions of devices to serve versatile location and case specific needs of vertical sectors in parallel with the provisioning of traditional mobile broadband services. As the majority of mobile traffic originates from indoors, cost-efficient and fast deployment of new indoor small cell networks is fundamental, which calls for new developments in regulation and technology to enable new business. This paper proposes the concept of micro operators (uO) for local service delivery in 5G to build indoor small cell communication infrastructure and offer context related services and content. Key elements of the new micro operator concept are introduced including regulation-related factors of local spectrum access rights, and technology-related factors of flexible network implementation. Several business opportunities are identified for the uO concept including the provisioning of hosted local connectivity to all MNOs in specific locations, operation of secure networks for vertical sector specific use, and offering of locally tailored content and services.

Bluetooth Indoor Positioning Based on RSSI and Kalman Filter

Abstract: In recent years, indoor positioning is becoming more and more important. Satellites can position only in the outdoor environment, which is unable to achieve precise positioning in the indoor environment. At present, the indoor positioning is mainly based on wireless signals, such as WiFi, RFID, Zigbee, Bluetooth etc. The cost and power consumption of using WiFi, RFID and Zigbee to realize the indoor positioning is very high and the deployment of WiFi, RFID and Zigbee is inconvenient. In this paper,indoor positioning is based on Bluetooth ibeacon, which is Bluetooth 4.0 standard. The power consumption and the cost of Bluetooth 4.0 is lower than others. In addition, Bluetooth has spread widely in the distance. This paper proposes a new indoor location method, which uses the method of learning to train the Bluetooth signal propagation model in the museum environment and uses the method of weighted least square and four-border positioning to estimate the location of the target object. The experimental result shows that the method is stable and good robustness. The positioning accuracy meets the requirements of the indoor positioning.

Path Observation Based Physical Routing Protocol for Wireless Ad Hoc Networks

Abstract: Wireless ad hoc networks are going to be an emerged multi-hop communication exploit among mobiles to deliver data packets The special characteristics of Wireless network make the communication link between mobiles to be unreliable To handle high mobility and environmental obstacles, most of physical routing protocols do not consider stable links during packet transmission which lead to higher delay and packet dropping in network In this paper, we propose path observation based physical routing protocol named POPR for WANET The proposed routing protocol incorporates relative distance, direction and mid-range forwarder node with traffic density to forward the data toward destination in order to improve physical forwarding between and at the intersection Simulation results show that the proposed routing protocol performs better as compared to existing solutions

A Survey of IoT Key Enabling and Future Technologies: 5G, Mobile IoT, Sematic Web and Applications

Abstract: The Internet of Things (IoT) is the communications paradigm that can provide the potential of ultimate communication. The IoT paradigm describes communication not only human to human (H2H) but also machine to machine (M2M) without the need of human interference. In this paper, we examine, review and present the current IoT technologies starting from the physical layer to the application and data layer. Additionally, we focus on future IoT key enabling technologies like the new fifth generation (5G) networks and Semantic Web. Finally, we present main IoT application domains like smart cities, transportation, logistics, and healthcare.

Advanced Indoor Positioning Using Zigbee Wireless Technology

Abstract: The paper presents the results of the project which examines the level of accuracy that can be achieved in precision indoor positioning using a new improved Zigbee network fingerprint method. This method can provide more accurate positioning by filtering algorithm for improving the fingerprint Zigbee database accuracy. In our experiment the following two steps have been completed. Firstly, we filtered out the interference data generated in the fingerprint database source data acquisition process what improved the accuracy of establishing the fingerprint database. Next, the nearest algorithm, the weighted nearest algorithm and Bayesian algorithm were used to calculate pedestrian’s location, and then the results are compared and analyzed. As a result, the average error with the improved fingerprint database is less than or equal to 0.81 m in a long distance range. The accuracy of the results got much better compared with the results without filtering. A newly developed ZigBee system by us can be applied to the location based services in a bigger space inside the buildings (distances up to 40 m) or in the underground mines.

Dynamic Multi-hop Clustering in a Wireless Sensor Network: Performance Improvement

Abstract: A cluster-based model is preferable in wireless sensor network due to its ability to reduce energy consumption. However, managing the nodes inside the cluster in a dynamic environment is an open challenge. Selecting the cluster heads (CHs) is a cumbersome process that greatly affects the network performance. Although there are several studies that propose CH selection methods, most of them are not appropriate for a dynamic clustering environment. To avoid this problem, several methods were proposed based on intelligent algorithms such as fuzzy logic, genetic algorithm (GA), and neural networks. However, these algorithms work better within a single-hop clustering model framework, and the network lifetime constitutes a big issue in case of multi-hop clustering environments. This paper introduces a new CH selection method based on GA for both single-hop and the multi-hop cluster models. The proposed method is designed to meet the requirements of dynamic environments by electing the CH based on six main features, namely, (1) the remaining energy, (2) the consumed energy, (3) the number of nearby neighbors, (4) the energy aware distance, (5) the node vulnerability, and (6) the degree of mobility. We shall see how the corresponding results show that the proposed algorithm greatly extends the network lifetime.

Cyber Security Threats to IoT Applications and Service Domains

Abstract: We are currently living in the post-PC era where smartphones and other wireless handheld devices are changing our environment, making it more interactive, adaptive and informative. Termed as Internet of Things (IoT) evolving into Internet of Everything, the new ecosystem combines wireless sensor networks, cloud computing, analytical data, interactive technologies, as well as smart devices, to provision solutions in which the objects are embedded with network connectivity and an identifier to enhance object-to-object interactions. IoT innovation is advancing and provides diverse smart solutions or applications. From e-transport to e-health; smart living to e-manufacturing and many other e-solutions. In this environment, the rising trend of cyber attacks on systems infrastructure coupled with the system inherent vulnerabilities presents a source of concern not only to the vendors, but also to the consumer. These security concerns need to be addressed in order to ensure user confidence so as to promote wide acceptance and reap the potentials of IoT. From the perspectives of firmware, hardware and software infrastructure setups, this paper looks at some of the major IoT application and service domains, and analyze the cybersecurity challenges which are likely to drive IoT research in the near future.

Adaptive KNN based Recommender System through Mining of User Preferences

Abstract: Research for the generation of reliable recommendations has been the main goal focused by many researchers in recent years. Though many recommendation approaches have been developed to assist users in the selection of their interesting items in the online world, still the personalization problem exists. In this paper, we present a new recommendation approach to address the problems such as scalability, sparsity, and cold-start in a collective way. We have developed a knowledge-based domain specific ontology for the generation of personalized recommendations. We have also introduced two different ontology-based predictive models as minion representation model and prominent representation model for the effective generation of recommendations to all types of users. The prediction models are induced by data mining algorithms by correlating the user preferences and features of items for user modeling. We have proposed a new variant of KNN algorithm as Adaptive KNN for the collaborative filtering based recommender system. The proposed recommendation approach is validated with standard MovieLens dataset and obtained results are evaluated with Precision, Recall, F-Measure, and Accuracy. The experimental results had proved the better performance of our proposed AKNN algorithm over other algorithms with the highly sparse data taken for the recommendation generation.

Performance Evaluation of SAC-OCDMA System in Free Space Optics and Optical Fiber System Based on Different Types of Codes

Abstract: In this paper, the Spectral Amplitude Coding-Optical Code Division Multiple Access (SAC-OCDMA) system performance is investigated both in Free Space Optics (FSO) and Optical Fiber Systems (OFS) scenarios focusing on different types of codes. The codes having low cross correlation such as Random Diagonal (RD) and Khazani-Syed (KS), and zero cross correlation such as Zero Cross Correlation (ZCC) and Multi-Diagonal (MD) are used. In the FSO scenario, moderate turbulence and hazy weather conditions are considered. In the OFS scenario, nonlinear effects, attenuation, and dispersion are taken into consideration. Also, the performance of various codes is evaluated under different rain attenuation conditions. The simulation results show that the SAC-OCDMA codes performance is media-dependent. The ZCC codes give better performance than low cross correlation codes in both FSO and OFS scenarios. The MD code gives the best code performance in both scenarios with the ZCC code following. The RD code provides better performance than the KS code in the OFS scenario. However, in the FSO scenario, the KS code performs better than the RD code under the turbulence effect. Furthermore, the MD code performance under different bit rates is investigated to support tri-play services. Its security performance is also investigated.

Robust and Secure Multiple Watermarking for Medical Images

Abstract: This paper presents a robust and secure region of interest and non-region of interest based watermarking method for medical images. The proposed method applies the combination of discrete wavelet transform and discrete cosine transforms on the cover medical image for the embedding of image and electronic patient records (EPR) watermark simultaneously. The embedding of multiple watermarks at the same time provides extra level of security and important for the patient identity verification purpose. Further, security of the image and EPR watermarks is enhancing by using message-digest (MD5) hash algorithm and Rivest---Shamir---Adleman respectively before embedding into the medical cover image. In addition, Hamming error correction code is applying on the encrypted EPR watermark to enhance the robustness and reduce the possibility bit error rates which may result into wrong diagnosis in medical environments. The robustness of the method is also extensively examined for known attacks such as salt & pepper, Gaussian, speckle, JPEG compression, filtering, histogram equalization. The method is found to be robust for hidden watermark at acceptable quality of the watermarked image. Therefore, the hybrid method is suitable for avoidance of the patient identity theft/alteration/modification and secure medical document dissemination over the open channel for medical applications.

Analyzing Throughput of MANET with Reduced Packet Loss

Abstract: This research paper analyses the throughput capacity of Mobile Ad hoc Network (MANET) with reduced packet loss. The nodes are then discovered using Medium Access Control (MAC) 802.11 protocol. It has the capability to discover the neighbor nodes automatically and the next node of the throughput for each node is determined using Flooding algorithm. In this algorithm, each node try to forward every information to every one of its nearest source node and then it receives the acknowledgement from the destination nodes. After initializing the source and destination node, the shortest path between the source and destination node is determined using K- Nearest Neighbor (KNN) algorithm. It calculates the distance between the nodes and sort the nearest neighbor based on the minimum distance. The routing is performed with the help of Dynamic Source Routing (DSR) algorithm which allows each dispatcher to decide on and control the routes used in routing packets. The packet loss gets reduced by considering the throughput of nodes. Here the Operating System is Linux Simulation software and then Network Simulator version 2 tool was used.

Performance Comparison and Detection Analysis in Snort and Suricata Environment

Abstract: Recently, crimes are cause in the internet by hacking to target one's and the companies financial. Due to the massive crimes that are caused by digital convergence and ubiquitous IT system, it is clear that the amount of network packet which need to be processed are rising. The digital convergence and ubiquitous IT system caused the IDS (Intrusion Detection System) to process packets more than the past. Snort (version 2.x) is a leading open source IDS which has a long history but since it was built a long time ago, it has several limitations which are not fit for today's requirements. Such as, it's processing unit is in single threading. On the other hand, Suricara was built to cover Snorts these disadvantages. To cover massive amount of packets which are caused by digital convergence and ubiquitous IT system Suricata's have the availability to process packets in multi-threading environment. In this paper we have analyzed and compared Snort and Suricata's processing and detection rate to decide which is better in single threading or multi-threading environment.

Energy-Efficient Hierarchical Routing for Wireless Sensor Networks: A Swarm Intelligence Approach

Abstract: Energy efficient routing in wireless sensor networks (WSNs) require non-conventional paradigm for design and development of power aware protocols. Swarm intelligence (SI) based metaheuristic can be applied for optimal routing of data, in an energy constraint WSNs environment. In this paper, we present BeeSwarm, a SI based energy-efficient hierarchical routing protocol for WSNs. Our protocol consists of three phases: (1) Set-up phase-BeeCluster, (2) Route discovery phase-BeeSearch and (3) Data transmission phase-BeeCarrier. Integration of three phases for clustering, data routing and transmission, is the key aspect of our proposed protocol, which ultimately contributes to its robustness. Evaluation of simulation results show that BeeSwarm perform better in terms of packet delivery, energy consumption and throughput with increased network life compared to other SI based hierarchical routing protocols.

Energy Aware Clustering Scheme in Wireless Sensor Network Using Neuro-Fuzzy Approach

Abstract: Nowadays sensor plays an important role in the day today life. People uses wireless technology along with sensor for monitoring home held devices, security alerts, natural disasters alert, building supervision, industrial quality management, etc. Wireless Sensor Network (WSN) consists of thousands of economical and feasible disposable sensors, deployed in the environment to sense parameters related to the surroundings such as temperature, moisture level, pressure etc., Number of sensor nodes are connected in these networks for communication. Each nodes are self-organized, having the capacity of sense, process, and aggregate data. Energy utilization in WSN is major issue in networks for improving network lifetime. Conventional clustering schemes are created with static cluster heads that die past than the normal nodes that degrade the network performance in routing. It is very vital area to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network life time. In this paper, a Energy Aware Clustering using Neuro-fuzzy approach (EACNF) is proposed to form finest and energy aware clusters. The proposed scheme consists of fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. EACNF used neural network that provide effective training set related to energy and density of all nodes to estimate the expected energy for Uncertain cluster heads. Sensor nodes with higher energy are trained with various location of base station to select energy aware cluster heads. Fuzzy if–then mapping rule is used in fuzzy logic part that inputs to form clusters and cluster heads. EACNF is designed for WSN that handling Trust factor for security to the network. EACNF used three metric such as transmission range, residual energy and Trust factor for improving network life time. The proposed scheme EACNF is compared with related clustering schemes namely Cluster-Head Election Mechanism using Fuzzy Logic and Energy-Aware Fuzzy Unequal Clustering. The experiment results show that EACNF performs better than the other related schemes.

An Improved Weighted K-Nearest Neighbor Algorithm for Indoor Positioning

Abstract: The weighted K-nearest neighbor algorithm (WKNN) is widely used in indoor positioning based on Wi-Fi. However, the accuracy of this traditional algorithm using Euclidean distance is not high enough due to the ignorance of statistical regularities from the training set. In this paper, the Manhattan distance is introduced to the WKNN algorithm to distinguish the influence of different reference nodes. Simultaneously, a new method is proposed to increase the accuracy of the algorithm by adjusting the weight of adjacent reference nodes. The simulation and experiment results show that the improved algorithm can have a better performance by increasing the accuracy by 33.82%.

Dynamic Self-Optimization of the Antenna Tilt for Best Trade-off Between Coverage and Capacity in Mobile Networks

Abstract: One major factor influencing the coverage and capacity in mobile networks is related to the configuration of the antennas and especially the antenna tilt angle By utilizing antenna tilt, signal reception within a cell can be improved and interference radiation towards other cells can be effectively reduced, which leads to a higher signal-to-interference-plus-noise ratio received by the users and increased sum data rate in the network In this work, a method for capacity and coverage optimization using base station antenna electrical tilt in mobile networks is proposed It has the potential to improve network performance while reducing operational costs and complexity, and to offer better quality of experience for the mobile users Our solution is based on the application of reinforcement learning and the simulation results show that the algorithm improves significantly the overall data rate of the network, as compared to no antenna tilt optimization The analysis in this paper focuses on the downlink of the cellular system For the simulation experiments a multicellular and sectorized mobile network in an urban environment and randomly distributed user terminals are considered The main contribution in this work is related to the development of a learning algorithm for automated antenna tilting

An Improved Remote User Authentication Scheme Using Elliptic Curve Cryptography

Abstract: Internet of Things has drastically expanded the global network for information exchange, because thousands of communication devices are becoming part of the global network. Besides the numerous benefits of global network expansion, secure communication and authentication among the comprising elements of the global network is also posing great challenges. Recently, Huang et al. proposed a key agreement scheme in order to facilitate user authenticity using elliptic curve cryptography. Huang et al. further emphasized the scheme is secure. Nevertheless, comprehensive analysis in this paper, demonstrates that Huang et al. scheme has correctness issues and is prone to impersonation/forgery attack. Then an improved scheme is presented to tenacity the said glitches existent in Huang et al.'s scheme. The security analysis of proposed scheme is substantiated in random oracle model. Furthermore, a simulation of proposed scheme is carried out by automated formal tool ProVerif. The performance and security assessments show that the scheme presented in this paper withstand impersonation attack and offers adequate security while reducing significant computation cost as compared with Huang et al.'s scheme. Hence, due to better performance and security, the proposed scheme is the appropriate one for security sensitive and resource constrained environments.

A Secure Smartcard-Based Anonymous User Authentication Scheme for Healthcare Applications Using Wireless Medical Sensor Networks

Abstract: A wireless medical sensor network (WMSN ) is a professional application of the traditional wireless body area sensor networks in medicine. Using WMSNs, the parameters of patients' vital signs can be gathered from the sensor nodes deployed on the body of the patients and accessed by the healthcare professionals by using a mobile device. Due to wireless communication, securing communication becomes a vital issue in WMSNs. Since the vital signs parameters are sensitive to the patients' health status and these information must not be revealed to the others except the healthcare professionals, the protection of patients' privacy becomes another key issue for WMSNs applications. Thus, user authentication with anonymity property is the most basic and commonly used method in order to resolve the security and privacy issues of WMSNs. He et al. presented a user authentication protocol for healthcare applications using WMSNs to protect the security and privacy problems. However, Li et al. showed that their scheme is incorrect in authentication and session key agreement phase, has no wrong password detection mechanism and is vulnerable to denial of service caused by password change with wrong password. In this paper, we review Li et al.'s scheme and show that their scheme is still vulnerable to privileged-insider attack, sensor node capture attack and fails to provide user anonymity property. Moreover, we find that He et al.'s scheme is still vulnerable to the same attacks as we find out in Li et al.'s scheme. In order to remedy the security weaknesses found in both He et al.'s scheme and Li et al.'s scheme, we present a secure biometrics-based user authentication scheme in WMSNs using smart card. Through the rigorous formal and informal security analysis, we show that our scheme is secure against possible known attacks. In addition, we simulate our scheme using the most-widely accepted and used Automated Validation of Internet Security Protocols and Applications tool and the simulation results reveal that our scheme is secure. Our scheme is also efficient in computation and communication as compared to He et al.'s scheme, Li et al.'s scheme and other related schemes.

Privacy Preserving Dynamic Pseudonym-Based Multiple Mix-Zones Authentication Protocol over Road Networks

Abstract: In this paper, we propose an efficient dynamic pseudonymous based multiple mix-zones authentication protocol for privacy preservation to enhance security over road networks. Most of the existing protocols either utilize pseudonym based approaches with certificate revocation list that cause significant communicational and storage overhead or they use group signature based approaches, which are computationally expensive. In this paper, we present a dynamic pseudonymous based multiple mix-zones authentication protocol that only requires mobile vehicles to communicate with reported server for registration and dynamic pseudonym change. Furthermore, we formulate a mechanism to provide users with dynamic pseudonyms named as; base pseudonyms and short time pseudonyms, to achieve users’ privacy. Finally, we analyze our protocol by determining the communication cost as well as various attack scenarios to prove that our approach is most efficient and robust as compared to existing techniques.

Review on MANET Based Communication for Search and Rescue Operations

Abstract: Mobile ad hoc networks (MANETs) are defined as a collection of wireless mobile nodes that are characterized as independent, dynamic, self-adaptive and infrastructure less. This mobility and dynamic in nature of MANET urge for new set of networking strategies to be implemented so as to provide efficient communication during natural disaster. Mobile crowd management is yet an emerging new exploration for search and rescue (SAR) operations. The phase of catastrophic management has communication to play a vital role. In MANETs, the end nodes communicate through the TCP/IP protocol. The layers of TCP/IP model change frequently due to mobility and resource overhead. This makes routing in MANETs one of the challenging research area. This review provides an overview of MANET based routing protocols employed for communication during SAR operations. The main purpose of this survey is to provide taxonomy on communication strategies of MANETs during disaster and emergency situation. Furthermore, this paper examines the existing MANET based SAR techniques and the significant contribution made by researches in the past few years based upon routing protocol, communication techniques, type of infrastructure and phase of disaster management.

A Novel Energy Efficient Stable Clustering Approach for Wireless Sensor Networks

Abstract: Wireless sensor network (WSN) consists of densely distributed nodes that are deployed to observe and react to events within the sensor field. In WSNs, energy management and network lifetime optimization are major issues in the designing of routing protocols. Clustering is an efficient data gathering technique that effectively reduces the energy consumption by organizing nodes into groups. However, in clustering protocols, cluster heads (CHs) bear additional load for coordinating various activities within the cluster. Improper selection of CHs causes increased energy consumption and also degrades the performance of WSN. Therefore, proper CH selection and their load balancing using efficient routing protocol is a critical aspect for the long run operation of WSN. Clustering a network with proper load balancing is an NP-hard problem. To solve such problems having vast search area, optimization algorithm is the preeminent possible solution. In this paper, differential evolution based clustering algorithm for WSNs named threshold-sensitive energy-efficient delay-aware routing protocol (TEDRP), is proposed to prolong network lifetime. Dual-hop communication between CHs and BS is utilized to achieve load balancing of distant CHs and energy minimization. The paper also considers stability-aware model of TEDRP named stable TEDRP (STEDRP) with an intend to extend the stability period of the network. In STEDRP, energy aware heuristics is applied for CH selection in order to improve the stability period. The results demonstrate that the proposed protocols significantly outperform existing protocols in terms of energy consumption, system lifetime and stability period.

Weighted Hyperbolic DV-Hop Positioning Node Localization Algorithm in WSNs

Abstract: The localization of nodes plays a fundamental role in Wireless Sensor and Actors Networks (WSAN) identifying geographically where an event occurred, which facilitates timely response to this action. This article presents a performance evaluation of multi-hop localization range-free algorithms used in WSAN, such as Distance Vector Hop (DV-Hop), Improved DV-Hop (IDV-Hop), and the Weighted DV-Hop (WDV-Hop). In addition, we propose a new localization algorithm, merging WDV-Hop, with the weighted hyperbolic localization algorithm (WH), which includes weights to the correlation matrix of the estimated distances between the node of interest (NOI) and the reference nodes (RN) in order to improve accuracy and precision. As performance metrics, the accuracy, precision, and computational complexity are evaluated. The algorithms are evaluated in three scenarios where all nodes are randomly distributed in a given area, varying the number of RNs, the density of nodes in the network, and radio coverage of the nodes. The results show that in networks with 100 nodes, WDV-Hop outperforms the DV-Hop and IDV-Hop even if the number of RNs is reduced to 10. Moreover, our proposal shows an improvement in terms of accuracy and precision at the cost of increased computational complexity, specifically in the algorithm execution time, but without affecting the hardware cost or power consumption.

Suitable Optical Fiber Communication Channel for Optical Nonlinearity Signal Processing in High Optical Data Rate Systems

Abstract: Our research presents best candidate different commercial optical fiber communication channel for optical nonlinearity signal processing in high optical transmission bit rate systems in the presence of traveling wave semiconductor optical amplifier (TW-OSA) These optical fibers that are namely dispersion flattened fiber (DFF), reverse dispersion fiber (RDF), non zero dispersion shifted fiber, dispersion compensated fiber, single mode fiber, and hybrid RDF + DFF Wavelength division multiplexing (WDM) system is employed to benefit 80 users with the high transmission bit rates up to 160 Gb/s over optical fiber communication channel length up to 200 km with trying to reduce nonlinearity effects by choosing suitable channel spacing and first or second order Bessel, Gaussian WDM Mux/Demux filter Maximum peak power, optical signal to noise ratio, and signal quality factor can be measured to test the system performance It is evident that RDF and hybrid RDF + DFF has presented the highest signal quality factor and optical nonlinearity signal processing in compared with other optical fibers communication channel The obtained results were done using optiwave system software simulation version 7

Multi-Objective WSN Deployment Using Genetic Algorithms Under Cost, Coverage, and Connectivity Constraints

Abstract: A wireless sensor network (WSN) deployment requires the identification of optimal network nodes (sensor and sink) positions in an area of interest, to ensure the best network performances (Senouci et al. in Smart Communications in Network Technologies (SaCoNeT), 2014 International Conference on, IEEE, pp 1---6, 43). The deployment process can be divided in two main parts: (1) WSN model construction, and (2) placement optimization. Few research works were interested by WSN deployment in indoor environment, even though, most of them consider the objectives (coverage, cost, connectivity) individually without considering the sensors and sink in the same time. This paper proposes a multi-objective deployment strategy (MODS), where all important objectives are integrated. The MODS uses the multi-objective evolutionary algorithms to get near optimal solution for WSN deployment problem. An original coding solution, integrating both network cost and nodes positions is proposed. A comparative study between two evolutionary strategies (classical GA, and NSGA-II) was performed to identify the use case of each one. Obtained results showed the interest of the proposed methodology.