scholarly journals MSSN: An Attribute-Aware Transmission Algorithm Exploiting Node Similarity for Opportunistic Social Networks

Information ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 299
Author(s):  
Mei Guo ◽  
Min Xiao
Keyword(s):  
Social Networks ◽  
Mobile Devices ◽  
Data Transmission ◽  
Routing Algorithms ◽  
Delivery Ratio ◽  
Relay Nodes ◽  
Similarity Degree ◽  
The Social ◽  
Node Similarity ◽  
End To End

Recently, with the development of big data and 5G networks, the number of intelligent mobile devices has increased dramatically, therefore the data that needs to be transmitted and processed in the networks has grown exponentially. It is difficult for the end-to-end communication mechanism proposed by traditional routing algorithms to implement the massive data transmission between mobile devices. Consequently, opportunistic social networks propose that the effective data transmission process could be implemented by selecting appropriate relay nodes. At present, most existing routing algorithms find suitable next-hop nodes by comparing the similarity degree between nodes. However, when evaluating the similarity between two mobile nodes, these routing algorithms either consider the mobility similarity between nodes, or only consider the social similarity between nodes. To improve the data dissemination environment, this paper proposes an effective data transmission strategy (MSSN) utilizing mobile and social similarities in opportunistic social networks. In our proposed strategy, we first calculate the mobile similarity between neighbor nodes and destination, set a mobile similarity threshold, and compute the social similarity between the nodes whose mobile similarity is greater than the threshold. The nodes with high mobile similarity degree to the destination node are the reliable relay nodes. After simulation experiments and comparison with other existing opportunistic social networks algorithms, the results show that the delivery ratio in the proposed algorithm is 0.80 on average, the average end-to-end delay is 23.1% lower than the FCNS algorithm (A fuzzy routing-forwarding algorithm exploiting comprehensive node similarity in opportunistic social networks), and the overhead on average is 14.9% lower than the Effective Information Transmission Based on Socialization Nodes (EIMST) algorithm.

scholarly journals Predict and Forward: An Efficient Routing-Delivery Scheme Based on Node Profile in Opportunistic Networks

2018 ◽  
Vol 10 (8) ◽  
pp. 74 ◽  
Author(s):  
Kanghuai Liu ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Yutong Xiao ◽  
Heng Zhang
Keyword(s):  
Opportunistic Networks ◽  
Routing Algorithms ◽  
Delivery Ratio ◽  
Complex Data ◽  
Relay Nodes ◽  
End To End Delay ◽  
The Social ◽  
Optimal Stopping Theory ◽  
Social Scene ◽  
End To End

In the social scene of opportunistic networks, message applications find suitable relay nodes or certain transmission destinations from the surrounding neighbors through specific network addresses of users. However, at the dawn of big data and 5G networks, the variational location information of nodes is difficult to be available to mobile devices all the time, and a long wait for the destination may cause severe end-to-end delay. To improve the transmission environment, this study constructs an efficient routing-delivery scheme (Predict and Forward) based on node profile for the opportunistic networks. The node profile effectively characterizes nodes by analyzing and comparing their attributes instead of network addresses, such as physical characteristics, places of residence, workplaces, occupations or hobbies. According to the optimal stopping theory, this algorithm implements the optimal transmission for Prelearn messages by dividing the complex data transmission process into two different phases (Predict and Forward). Through simulations and the comparison of routing algorithms in opportunistic networks, the proposed strategy increases the delivery ratio by 80% with the traditional methods on average, and the average end-to-end delay in this algorithm is the lowest.

scholarly journals FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks

Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 338 ◽  
Author(s):  
Kanghuai Liu ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Leilei Wang
Keyword(s):  
Social Networks ◽  
Data Transmission ◽  
Contextual Information ◽  
Relay Node ◽  
Feedback Mechanism ◽  
Delivery Ratio ◽  
Fuzzy Evaluation ◽  
Message Delivery ◽  
Transmission Process ◽  
Node Similarity

At the dawn of big data and 5G networks, end-to-end communication with large amounts of data between mobile devices is difficult to be implemented through the traditional face-to-face transmission mechanism in social networks. Consequently, opportunistic social networks proposed that message applications should choose proper relay nodes to perform effective data transmission processes. At present, several routing algorithms, based on node similarity, attempt to use the contextual information related to nodes and the special relationships between them to select a suitable relay node among neighbors. However, when evaluating the similarity degree between a pair of nodes, most existing algorithms in opportunistic social networks pay attention to only a few similar factors, and even ignore the importance of mobile similarity in the data transmission process. To improve the transmission environment, this study establishes a fuzzy routing-forwarding algorithm (FCNS) exploiting comprehensive node similarity (the mobile and social similarities) in opportunistic social networks. In our proposed scheme, the transmission preference of the node is determined through the fuzzy evaluation of mobile and social similarities. The suitable message delivery decision is made by collecting and comparing the transmission preference of nodes, and the sustainable and stable data transmission process is performed through the feedback mechanism. Through simulations and the comparison of social network algorithms, the delivery ratio in the proposed algorithm is 0.85 on average, and the routing delay and network overhead of this algorithm are always the lowest.

A time for play: Interstitial time, Invest/Express games, and feminine leisure style

2016 ◽  
Vol 20 (1) ◽  
pp. 105-121 ◽  
Author(s):  
Shira Chess
Keyword(s):  
Social Networks ◽  
Video Games ◽  
Social Networking ◽  
Mobile Devices ◽  
Social Relationships ◽  
Social Aspects ◽  
The Social

Games such as FarmVille and other casuals played on social networks and mobile devices have recently become increasingly popular. Research on Social Networking Games (SNGs) often focuses on the “social” aspects—how this newer style of games engenders social relationships from disparate locations. This essay examines the genre of gaming in terms of their industry category, “Invest/Express Games.” Using the Invest/Express label as a means of rethinking the role of interstitial time, this essay proposes that the gaming style taps in to what can be understood as “feminine leisure style.” In many ways, the significance of Invest/Express embodies a shift toward a feminization of popular video games.

scholarly journals A Combined Modified OpportunisticNeighbor Selection and Vehicle Localization Routing Approach for Improved Connectivity in Indian Road Scenario

2018 ◽  
Vol 7 (3.16) ◽  
pp. 52
Author(s):  
Jothy. N ◽  
Jayanthi. K ◽  
Gunasundari. R
Keyword(s):  
High Mobility ◽  
Routing Algorithms ◽  
Link Quality ◽  
Delivery Ratio ◽  
Network Partitioning ◽  
Vehicle Localization ◽  
End To End Delay ◽  
End To End ◽  
Neighbor Selection ◽  
Link Availability

In the recent years, VANET is becoming a spectacular research area in wireless networks. The high mobility vehicular node in VANET dynamically changes the network topology resulting in highly unstable vehicle connectivity. This induces network partitioning and hence ensuring link availability remains to be a challenging task.  To surpass these issues, design of efficient VANET routing algorithms is necessary. The routing design for VANET scenario is highly complex and challenging making the existing AODV, greedy, cluster based routing algorithms to suffer from degraded link quality resulting in high end-to-end delay and significant packet loss. Although Opportunistic Neighbor Selection (ONS) scheme proves to be a better routing logic, it does not seem to always ensure link availability at road intersections, particularly in Indian road scenario, where multi road lane discipline is very hard to implement. To overcome these limitations, a combination of Modified Opportunistic Neighbor Selection (MONS) and Vehicle Localization (VL) routing logic for adoption in Indian road sector has been proposed in this paper. This paper addresses the connectivity challenges and provides better solution to achieve improved performance. In this work, two specific scenarios namely: varied mobility/node density rates is considered by treating the other fixed inorder to evaluate the suitability of the proposed logic in terms of packet delivery ratio, end-to-end delay.  

scholarly journals Location prediction in location-based social networks

2017 ◽  
Vol 7 (3) ◽  
pp. 149-156
Author(s):  
Mucahit Baydar ◽  
Songul Albayrak
Keyword(s):  
Social Networks ◽  
Wireless Networks ◽  
Social Network ◽  
Mobile Devices ◽  
New Method ◽  
Time Range ◽  
Location Prediction ◽  
The Social ◽  
Location Based Social Network ◽  
Location Based Social Networks

AbstractDevelopments in mobile devices and wireless networks have led to the increasing popularity of location-based social networks. These networks allow users to explore new places, share their location, videos and photos and make friends. They give information about the mobility of users, which can be used to improve the networks. This paper studies the problem of predicting the next check-in of users of location-based social networks. For an accurate prediction, we first analyse the datasets that are obtained from the social networks, Foursquare and Gowalla. Then we obtain some features like place popularity, place popular time range, place distance to user’s home, user’s past visits, category preferences and friendships ,which are used for prediction and deeper understanding of the user behaviours. We use each feature individually, and then in combination, using the new method. Finally, we compare the acquired results and observe the improvement with the new method.Keywords: Location prediction, location-based social network, check-in data.

scholarly journals Privacy study on images uploaded in social networks

2018 ◽  
Vol 7 (1.7) ◽  
pp. 142
Author(s):  
Hemalatha D ◽  
Almas Begum ◽  
Alex David S
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Mobile Devices ◽  
Public Interest ◽  
Online Social Networks ◽  
Personal Information ◽  
Personal Characteristics ◽  
The Social ◽  
Study Results ◽  
Privacy Settings

Presently, the growth of Social media is explosive among the users. Increasingly developed social websites like Flickr, Facebook, Google+, LinkedIn etc permits the users to create, share and view the post. Confidentiality is a leading factor required in Social Networks. The social users upload their photos to the social sites that intend to gain public interest for social purposes. The exposure of personal information leads to slipping process like identity stealing, morphing etc, which are against the privacy violations. Relied upon the personal characteristics of users, the privacy settings of each user should be defined. In this paper, a relational study about the privacy settings in Online Social structure is examined. Initiated by the importance of social networks among the social users and their behavior towards Online Social Networks, which is followed by the privacy techniques suggested by other researchers are explored. At last, an overview about the merits and demerits of privacy designs and schemes for the user-uploaded images are presented. The study results a new privacy system that controls the confidential information from being accessed from different devices, including mobile devices and computers.

scholarly journals Multi-Token Based MAC-Cum-Routing Protocol for WSN: A Distributed Approach

2019 ◽  
Vol 15 (3) ◽  
Author(s):  
Subhasis Dash ◽  
Saras Kumar ◽  
Manas Ranjan Lenka ◽  
Amulya Ratna Swain
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Data Transmission ◽  
Mac Protocol ◽  
Reliable Data ◽  
Packet Delivery Ratio ◽  
Delivery Ratio ◽  
Data Delivery ◽  
Packet Delivery ◽  
End To End

A wireless sensor network is a collection of batterypowered sensor nodes distributed in a geographical area. Inmany applications, such networks are left unattended for along period of time. These networks suffer from the problemslike high energy consumption, high latency time, and end- to-end low packet delivery ratio. To design a protocol that findsa trade-off between these problems is a challenging task. Inorder to mitigate energy consumption issue, different existingMedia Access Control (MAC) protocols such as S-MAC, RMAC,HEMAC, and Congestion-less Single Token MAC protocols havebeen proposed which ensure better packet delivery but fail toensure energy efficiency due to high end-to-end latency. Theproblem of high end-to-end latency is resolved with the existingrouting protocols such as Fault Tolerant Multilevel Routingprotocol (FMS)and Enhanced Tree Routing (ETR) protocol.AS2-MAC and Multi Token based MAC protocol are able toimprove the end-to-end packet delivery ratio. However, thehierarchical network structure used in these protocols increasestime and energy consumption during network reconstruction.This problem was further resolved in Distributed HierarchicalStructure Routing protocol by constructing the network structurein a distributed manner. In all these existing protocols, efficienttoken management and reliable data delivery ratio was notproperly addressed, which in turn consume more energy. So,it is clear that MAC and routing protocols both together cangive better results related to data transmission in WSN. Inorder to achieve the same, in this paper, we propose a reliabledata transmission algorithm that satisfies both routing and MACprotocol to improve the end-to-end data delivery. The proposedprotocol uses different control message exchange that ensures datapacket delivery in each individual levels and it ultimately uses oftokens to ensure reliable data transmission along with reducedtraffic congestion during end-to-end data delivery. The algorithmconsiderably improves the packet delivery ratio along with reduceenergy consumption of each sensor node. Simulation studies ofthe proposed approach have been carried out and its performancehas been compared with the Multi Token based MAC protocol,AS-MAC protocol and ETR routing protocol. The experimentalresults based on simulation confirms that the proposed approachhas a higher data packet delivery ratio.

Social-aware data dissemination in opportunistic mobile social networks

2017 ◽  
Vol 28 (09) ◽  
pp. 1750115 ◽  
Author(s):  
Yibo Yang ◽  
Honglin Zhao ◽  
Jinlong Ma ◽  
Xiaowei Han
Keyword(s):  
Social Networks ◽  
Data Dissemination ◽  
Geographical Information ◽  
Communication Overhead ◽  
Delivery Ratio ◽  
Mobile Social Networks ◽  
Relay Nodes ◽  
Data Propagation ◽  
Contact Frequency ◽  
Opportunistic Mobile Social Networks

Opportunistic Mobile Social Networks (OMSNs), formed by mobile users with social relationships and characteristics, enhance spontaneous communication among users that opportunistically encounter each other. Such networks can be exploited to improve the performance of data forwarding. Discovering optimal relay nodes is one of the important issues for efficient data propagation in OMSNs. Although traditional centrality definitions to identify the nodes features in network, they cannot identify effectively the influential nodes for data dissemination in OMSNs. Existing protocols take advantage of spatial contact frequency and social characteristics to enhance transmission performance. However, existing protocols have not fully exploited the benefits of the relations and the effects between geographical information, social features and user interests. In this paper, we first evaluate these three characteristics of users and design a routing protocol called Geo-Social-Interest (GSI) protocol to select optimal relay nodes. We compare the performance of GSI using real INFOCOM06 data sets. The experiment results demonstrate that GSI overperforms the other protocols with highest data delivery ratio and low communication overhead.

ChronoFindMe

2013 ◽  
pp. 171-187
Author(s):  
Ana Filipa Nogueira ◽  
Catarina Silva
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Mobile Devices ◽  
Mobile Application ◽  
Location Based Services ◽  
User Experiences ◽  
Mobile Interaction ◽  
The Past ◽  
The Social ◽  
Geographical Position

Social networks such as Facebook have grown exponentially over the past decade. This growth led to the exploration of new services that could enhance users’ experiences and constitute a driver for even more followers. With the proliferation of smartphones and the increasing search for applications that enable the sharing of experiences, social networks became eager to integrate into mobile devices, taking advantage of their impressive omnipresence and panoply of sensors. Amongst the sensors, the most notable are the localization sensors (GPS) that allow for the development of location-based services that use the geographical position to enrich user experiences in a variety of contexts, including location-based searching and location-based mobile interaction. ChronoFindMe enhances location-based services by adding a temporal component not present in current approaches. The authors allow information about past and future locations to be considered by defining an architecture that provides location-based services to users of social networks. This information includes data about time and space, which can be accessed through the social network or a specific mobile application, using privacy policies to assure users’ privacy.

scholarly journals A Transmission Prediction Neighbor Mechanism Based on a Mixed Probability Model in an Opportunistic Complex Social Network

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 600 ◽  
Author(s):  
Genghua Yu ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Jian Wu
Keyword(s):  
Social Networks ◽  
Data Transmission ◽  
Probability Model ◽  
Routing Algorithm ◽  
Large Data ◽  
Complex Data ◽  
Message Delivery ◽  
Hop Count ◽  
Prediction Result ◽  
The Social

The amount of data has skyrocketed in Fifth-generation (5G) networks. How to select an appropriate node to transmit information is important when we analyze complex data in 5G communication. We could sophisticate decision-making methods for more convenient data transmission, and opportunistic complex social networks play an increasingly important role. Users can adopt it for information sharing and data transmission. However, the encountering of nodes in mobile opportunistic network is random. The latest probabilistic routing method may not consider the social and cooperative nature of nodes, and could not be well applied to the large data transmission problem of social networks. Thus, we quantify the social and cooperative relationships symmetrically between the mobile devices themselves and the nodes, and then propose a routing algorithm based on an improved probability model to predict the probability of encounters between nodes (PEBN). Since our algorithm comprehensively considers the social relationship and cooperation relationship between nodes, the prediction result of the target node can also be given without encountering information. The neighbor nodes with higher probability are filtered by the prediction result. In the experiment, we set the node’s selfishness randomly. The simulation results show that compared with other state-of-art transmission models, our algorithm has significantly improved the message delivery rate, hop count, and overhead.

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