Cognitive radio networks (CRN), in their quest to become the preferred next-generation wireless communication paradigm, will depend heavily on their ability to efficiently manage the limited resources at their disposal in meeting the demands of their numerous users and driving their operations. As a result, a considerable amount of research work has been recently dedicated to investigating and developing resource allocation (RA) models that capture the essentials of CRN. The various ideas put forward by researchers to address RA problems in CRN have been somewhat diverse, and somehow, there seem to be no links that bring cohesion and clarity of purpose and ideas. To address this problem and bridge the gap, in this paper, a comprehensive study on the prevalent techniques developed for addressing RA problems in CRN is carried out, with an intent to put some structure, relevance and meaning to the various solution approaches. The solution models are therefore grouped and/or classified based on certain outstanding criteria, and their strengths and weaknesses highlighted. Open-ended problems are identified, and suggestions for improving solution models are given. The study therefore gives good directions for further investigations on developing RA solutions in CRN.

/pdf/solving-resource-allocation-problems-in-cognitive-radio-3rrvehjom4.pdf

Solving resource allocation problems in cognitive radio networks : a survey

Recent advances in artificial intelligence, big data, mobile edge computing and embedded systems have successfully driven the emergence and adoption of smart vehicles and vehicle edge computing which will improve road safety, traffic congestions, and vehicle exhaust emissions. The high-mobility, ad-hoc network topology, and diverse vehicle-to-everything (V2X) have brought substantial challenges in the TCP/IP-based vehicular networking. Given the unique characteristics and strengths in resilient communication in mobile ad hoc networking environments, named data networking (NDN) has become a natural fit for supporting vehicular edge computing (VEC) as the underlying network architecture. However, a variety of security and privacy challenges remain for developing NDN-based VEC networks such as key management, cache poisoning, access control. In this paper, we introduce a novel blockchain-based security architecture in NDN-based VEC networks to systematically tackle these security challenges. More specifically, we design and implement an efficient blockchain system on NDN by adopting lightweight yet robust delegate consensus algorithm, and carry out extensive experiments to evaluate performance efficiency on key management protocols, cache poisoning defense schemes, and access control strategies for NDN-based VEC networks. To the best of our knowledge, this paper is the first effort to systematically devise practical and efficient blockchain-based security architecture to provide key management, cache poisoning security protection, and privacy-aware access control in NDN VEC networks.

Blockchain-Based Cache Poisoning Security Protection and Privacy-Aware Access Control in NDN Vehicular Edge Computing Networks

The sensor nodes in wireless sensor networks (WSNs). inherit low processing, shorter range and low power features with the miniature size to offer wireless transmission. Therefore, in order to fulfil the long-time data sensing need, several Quality of Service (QoS) parameters such as: lesser delay, higher throughput and packet delivery ratio (PDR) with minimum overhead must to be improved. In recent years extensive research efforts have been made to ameliorate these parameters to achieve optimum QoS. However, the rate adaptation and congestion control in WSNs are still least explored areas. The traffic congestion in WSNs is the main reason that results in higher delay and low throughput. In this paper, a new rate aware congestion control (RACC) mechanism has been proposed which defines three levels of congestion based on which the data rate, throughput, overhead and the delay. RACC at the transport layer, improves congestion by source rate regulation at the specific hotspot areas. Further, RACC has been applied to different modulation schemes like: 16 QAM (Quadrature Amplitude Modulation), BPSK (Binary Phase Shift Keying) and QPSK (Quadrature Phase Shift Keying) to test the optimum modulation scheme for the proposed approach. The testing is done to ensure the that the data can be sent to the longer distant sensors using appropriate modulation technique suitable for the congestion model (RACC). The simulation outcomes in NS2 tool confirms the improvement of RACC over existing techniques (Delay-aware congestion control protocol (DACC) and Joint energy replenishment and load balancing (J-ERLB)) in WSNs. The overall improvement for RACC over existing techniques follows an improvement percentage 17% for throughput parameter, for packet delivery ratio, it is 8.35%, while for normalized routing overhead it shows 0.56% and for MAC Overhead, average end to end delay, and average remaining energy it shows 0.64%, 2.04% and 59.28% improvement respectively.

Rate aware congestion control mechanism for wireless sensor networks

The autonomous cache management in Content-Centric Networking (CCN) results in suboptimal caching decisions and implies cache-ignorant routing. Cache coordination and similar improvements hence have been the subject of several
recent studies. The proposed solutions, however, are either impractical due to their massive coordination overhead, or of
limited benefit since they cannot realize perfect coordination.

We present CoMon, an architecture for network-wide coordinated caching. CoMon realizes an affordable, yet highly
effective, coordination by assigning monitoring and cache-aware (re)routing tasks to only a few nodes, through which the majority of traffic is expected or enforced to pass. CoMon, by design, can maximize the diversity of cached contents and minimize cache replacements. In addition, our simulation study using ISP topologies, shows that CoMon under a
pressuring scenario, when coordinates as few as 5% of the nodes, reduces the server hit ratio of both CCN and notable related work by up to 45%. 

Index Terms: Information-Centric Networking; Coordinated Caching; Cache-Aware Routing

CoMon: An Architecture for Coordinated Caching and Cache-Aware Routing in CCN (to appear)

Congestion in wireless sensor networks (WSNs) is an unavoidable issue in today’s scenario, where data traffic increased to its aggregated capacity of the channel. The consequence of this turns in to overflowing of the buffer at each receiving sensor nodes which ultimately drops the packets, reduces the packet delivery ratio, and degrades throughput of the network, since retransmission of every unacknowledged packet is not an optimized solution in terms of energy for resource-restricted sensor nodes. Routing is one of the most preferred approaches for minimizing the energy consumption of nodes and enhancing the throughput in WSNs, since the routing problem has been proved to be an NP-hard and it has been realized that a heuristic-based approach provides better performance than their traditional counterparts. To tackle all the mentioned issues, this paper proposes an efficient congestion avoidance approach using Huffman coding algorithm and ant colony optimization (ECA-HA) to improve the network performance. This approach is a combination of traffic-oriented and resource-oriented optimization. Specially, ant colony optimization has been employed to find multiple congestion-free alternate paths. The forward ant constructs multiple congestion-free paths from source to sink node, and backward ant ensures about the successful creation of paths moving from sink to source node, considering energy of the link, packet loss rate, and congestion level. Huffman coding considers the packet loss rate on different alternate paths discovered by ant colony optimization for selection of an optimal path. Finally, the simulation result presents that the proposed approach outperforms the state of the art approaches in terms of average energy consumption, delay, and throughput and packet delivery ratio.

/pdf/traffic-and-energy-aware-optimization-for-congestion-control-20p9dyqpnu.pdf

Traffic and Energy Aware Optimization for Congestion Control in Next Generation Wireless Sensor Networks

A Walkthrough of Name Data Networking: Architecture, Functionalities, Operations and Open issues

Online banking (or Internet baking or E-banking) makes people capable to do financial transactions on a secured website It allows users to manage their money without going to their respective banks Today, the users can do the financial transactions of their daily life like bill payments, shopping, booking movie, train, air and various other event tickets through online banking Since the online banking involves circulation of money so it should be secured but as the use of online banking is increasing, the security threats to the banking applications are also increasing In this paper, we have designed a Java based tool to show the exploitation of Injection (OWASP Top 10-2013 A1 Vulnerability) using SQL Injection attack and Broken Authentication(part of OWASP Top 10-2013 A2 Vulnerability) using Brute Force Attack and Dictionary Attack and the prevention of all these attack by storing the data in our database in encrypted form using AES algorithm

CAVEAT: Credit Card Vulnerability Exhibition and Authentication Tool

Assessment of security threat for Internet has become a major concern because of the advancement and expansion of IT in recent years, and it is equally important for future Internet architectures. Name data networking architecture is designed from scratch and is immune to most of the security attacks that are common in IP-based networks. The newly added features give rise to new security attacks which can compromise user privacy, data confidentiality, and integrity. Formal mathematical modeling is essential for proper assessments and mitigation from the security attacks. Security attack modeling provides insight of network vulnerabilities and helps in identifying the areas, which have to be kept on priority. This paper presents an attack tree-based privacy attack modeling and risk assessment technique for NDN. First attack tree is constructed in a top-down approach to find out possible attacks and threats that compromise user privacy from the attacker’s point of view and then presented risk assessment technique to ascertain degree of threat that an attack imposes on user privacy.

Privacy Attack Modeling and Risk Assessment Method for Name Data Networking

A wireless sensor network is gaining more popularity as it is easy to maintain, manage and inexpensive to establish. A group of sensor nodes with sensing and computing capability are deployed in ne...

R. L. Ujjwal

Papers

A Walkthrough of Name Data Networking: Architecture, Functionalities, Operations and Open issues

Traffic and Energy Aware Optimization for Congestion Control in Next Generation Wireless Sensor Networks

CAVEAT: Credit Card Vulnerability Exhibition and Authentication Tool

Privacy Attack Modeling and Risk Assessment Method for Name Data Networking

Sensor data fusion and clustering : A congestion detection and avoidance approach in wireless sensor networks