Sudhakar Pandey

Efficient Resource Management by Exploiting D2D Communication for 5G Networks

Device-to-device (D2D) communication is a promising technology for 5G networks, providing high data rates, increased spectral and energy efficiency, and reduced end-to-end delay and transmission power. However, in current cellular systems, the performance of cell edge devices suffers when multimedia content is directly uploaded toward the base station side due to poor link quality. This requires a greater number of resource blocks and additional upload time, thus degrading the quality of service. To reduce the number of resource blocks and upload time, this paper proposes an efficient resource management scheme that exploits D2D communication in the uplink case. This scheme consists of two phases. In the first phase, in the case of poor link quality, a novel relay selection scheme is used in the multihop (two-hop) communication strategy; in the second phase, an effective new resource allocation scheme is used in multihop communication. This scheme minimizes packet loss, upload time, and number of resource blocks, whereas it increases the throughput of the network. Simulation result demonstrates the superiority of the proposed scheme over other schemes in the literature.

A Device-Centric Scheme for Relay Selection in a Dynamic Network Scenario for 5G Communication

Device-centric architecture is an aspect of fifth generation communication whereby devices/user equipment is able to directly communicate with other devices with minimal involvement by the base station (BS). However, devices that are not within their proximity area communicate with other devices (relay). In this paper, we propose a device-centric scheme for relay selection in a dynamic network scenario. In this scheme, once the communicating devices have reached the maximum distance threshold, they exchange neighbor tables and find common devices (relay) for further communication. In addition, we propose a new relay selection scheme for scenarios, where the devices have more than one device (relay) in common. The proposed relay selection scheme is based on several parameters, including signal-to-noise ratio (SNR), signal-to-interference plus noise ratio, residual battery power, buffer space, and reliability; this provides more reliable and efficient communication. The current relay schemes, including max-min and max-max, are network assisted; the network/BS decides the relay, which increases the load on the BS side. The BS selects relay based on channel state information or SNR, which does not provide efficient or reliable communication. Our proposed device-centric scheme depends less on the BS during relay selection, which reduces network overhead, and the relay selection scheme provides more efficient and reliable communication. A comparison with other relay selection schemes shows that our scheme is 30% more effective in each case.

Folksonomy Based Trend Analysis on Community Question Answering Sites: A Perspective on Software Technologies

In the booming era of online social media environment, community question answering (CQA) sites have become one of the popular resources for software engineers and software industries. Software engineers are increasingly sharing their questions and answers on CQA sites. Aims of the CQA sites are to provide useful and relevant information to the users. Analysis information of major programming languages using trend analysis can be useful for software engineers to understand the technological evolutions and popularity. Since most of the CQA sites consist of user assigned tags by which folksonomy can be efficiently utilized for developing suitable algorithm to find the trend of key programming technologies. In this paper, two techniques of trend analysis, namely, ARIMA time series model and fuzzy time series model have been applied on the tagging data to identify the trend. Trend analysis is being carried on key programming languages, namely, c#, Java, PHP, and python. In this paper, quality of the trend is measured by entropy, ZTrend, and quality of forecast is measured by MMRE, burst trend for key programming languages.

Device-centric resource allocation scheme for 5G networks

Abstract Device-centric architecture is an important aspect for fifth generation (5G) networks. The current cellular systems are base station-centric where the base-station (BS) is responsible for resource allocation. The BS allocates resources to users based on their channel state information (CSI) and feedback. This resource allocation process increases load at the BS side resulting in more time consumption. This decreases the overall network throughput and increases delay in resource allocation. Therefore, in this article, a device-centric resource allocation scheme is proposed for D2D users. In this scheme, interested D2D pairs can allocate the resource to themselves using the following three steps. In first step, devices maintain their resource occupancy matrix by exchanging the neighbouring information. In second step, a resource block is selected based on resource allocation scenarios. In third steps, resource block is allocated based on the priority on the BS side. The proposed scheme is less dependent on the BS side, hence it reduces the load on BS side and it also reduces time consumption in resource allocation process. Additionally, the proposed scheme improves the overall network throughput. A comparison of the proposed scheme with the base-centric scheme shows that proposed scheme is up to 35% more effective in each experimental case.

FUCA: Fuzzy‐based unequal clustering algorithm to prolong the lifetime of wireless sensor networks

Summary Wireless sensor network comprises billions of nodes that work collaboratively, gather data, and transmit to the sink. “Energy hole” or “hotspot” problem is a phenomenon in which nodes near to the sink die prematurely, which causes the network partition. This is because of the imbalance of the consumption of energy by the nodes in wireless sensor networks. This decreases the networks lifetime. Unequal clustering is a technique to cope up with this issue. In this paper, an algorithm, “fuzzy-based unequal clustering algorithm,” is proposed to prolong the lifetime of the network. This protocol forms unequal clusters. This is to balance the energy consumption. Cluster head selection is done through fuzzy logic approach. Input variables are the distance to base station, residual energy, and density. Competition radius and rank are the two output fuzzy variables. Mamdani method is employed for fuzzy inference. The protocol is compared with well-known algorithms, like low-energy adaptive clustering hierarchy, energy-aware unequal clustering fuzzy, multi-objective fuzzy clustering algorithm, and fuzzy-based unequal clustering under different network scenarios. In all the scenarios, the proposed protocol performs better. It extends the lifetime of the network as compared with its counterparts.

Improved Prophet Routing Algorithm for Opportunistic Networks

The Delay Tolerant Network paradigm was proposed to address communication issues in challenged environments where no end-to-end connectivity exists. DTN is called Opportunistic Network as intermediate node always looks for the best opportunity to relay a message from source to destination. In Vehicular Delay Tolerant networks, some nodes follow a fixed path while others follow a random path. In this paper, after the study and analysis of various protocols, a new protocol has been proposed by making changes in PRoPHET Routing Algorithm to maximize and improve the delivery probability and minimize the number of messages being dropped and the overhead ratio. A comparison has been provided between the original and proposed PRoPHET Algorithm.

An Efficient Data Aggregation Algorithm with Gossiping for Smart Transportation System

As there is a continuous increase in number of vehicles in urban as well as rural areas, the congestion of vehicles is becoming a very big problem. Smart transportation systems are used to collect information about existing traffic on roads. Wireless sensor networks offer better performance and reduced cost when used in the smart transportation system. Data aggregation algorithms can be used to reduce sensor network congestion. This paper discusses the use of wireless sensor networks for smart transportation system and data aggregation algorithm to reduce the network traffic. In this paper, we used hybrid data aggregation algorithm with gossiping incorporating mobility of nodes. We evaluated the performance of proposed scheme with the existing hybrid aggregation algorithm. The result analysis shows that proposed scheme is efficient and scalable.

Hybrid Resource Allocation Scheme in Multi-hop Device-to-Device Communication for 5G Networks

AbstractThe 5G communication paradigm provides architecture of coexistence of device-to-device (D2D) communication with the current cellular communication. Direct D2D communication offloads the major traffic by enabling the localized communication between the users with the advantage of close proximity by reusing cellular resource block. However, direct D2D communication suffers from limited proximity constraint. In order to increase the proximity, direct D2D communication can be extended to multi-hop D2D communication. By sharing the cellular resource with multi-hop D2D pairs, a significant interference may occur that further reduces the system throughput. In order to reduce the interference and to increase the throughput of the network, a hybrid resource allocation scheme for the multi-hop D2D communication is proposed in this work. This scheme is divided into two parts. In first part, an interference matrix is constructed by using graph-based technique. Particle swarm optimization (PSO) algorithm is applied in second part. The application of PSO not only reduces the interference at significant level but also harvests true potential gains of each resource block with improved overall throughput of the system. The extensive simulation results demonstrate the effectiveness of the proposed scheme with the random resource allocation scheme and graph-based resource allocation scheme. In addition, proposed scheme performs better in case of increased proximity and supports the minimum data rate compared to the orthogonal sharing-based resource allocation and cellular-oriented resource allocation schemes.

A user ranking algorithm for efficient information management of community sites using spectral clustering and folksonomy

Community question answering (CQA) sites are the major platform for information sharing where posts are created by users as questions and answers. A large number of posts are created on a day-to-day basis, which raise the problem of information management of these sites. Multiple techniques are suggested in existing research for efficient management of CQA sites. Many of the existing techniques used the user ranking for managing the CQA sites but ignored the tagging data and user subject area. In this article, a user ranking method is derived using spectral clustering for posts management by considering the tagging data of CQA sites. Folksonomy is used to build relationship between tags, posts and users. The proposed method is developed in three stages. In first stage, the folksonomy relation is created and user similarity graph is built with the help of tag frequency-inverse post frequency and text similarity techniques. In the second stage, spectral clustering algorithm is applied on user similarity graph to group the similar users. Finally, in third stage, rank of users is identified from the clusters based on user’s information. The clustered users and rank of the users are generated as the output of the proposed algorithm that can provide a way of efficient information management. The experimental results show that the proposed user ranking algorithm outperforms the other considered ranking algorithms and can be helpful for information management of CQA sites. Some real-life applications of information management in CQA sites using the proposed work are also demonstrated in this article.

RANKuser: A folksonomy and user profile based algorithm to identify experts in Community Question Answering sites

Purpose Recently, with a high volume of users and user’s content in Community Question Answering (CQA) sites, the quality of answers provided by users has raised a big concern. Finding the expert users can be a method to address this problem, which aims to find the suitable users (answerers) who can provide high-quality relevant answers. The purpose of this paper is to find the expert users for the newly posted questions of the CQA sites. Design/methodology/approach In this paper, a new algorithm, RANKuser, is proposed for identifying the expert users of CQA sites. The proposed RANKuser algorithm consists of three major stages. In the first stage, folksonomy relation between users, tags, and queries is established. User profile attributes, namely, reputation, tags, and badges, are also considered in folksonomy. In the second stage, expertise scores of the user are calculated based on reputation, badges, and tags. Finally, in the third stage, the expert users are identified by extracting top N users based on expertise score. Findings In this work, with the help of proposed ranking algorithm, expert users are identified for newly posted questions. In this paper, comparison of proposed user ranking algorithm (RANKuser) is also performed with other existing ranking algorithms, namely, ML-KNN, rankSVM, LDA, STM CQARank, and EV-based model using performance parameters such as hamming loss, accuracy, average precision, one error, F-measure, and normalized discounted cumulative gain. The proposed ranking method is also compared to the original ranking of CQA sites using the paired t-test. The experimental results demonstrate the effectiveness of the proposed RANKuser algorithm in comparison with the existing ranking algorithms. Originality/value This paper proposes and implements a new algorithm for expert user identification in CQA sites. By utilizing the folksonomy in CQA sites and information of user profile, this algorithm identifies the experts.