Towards the Realization of Decentralized Online Social Networks: An Empirical Study

Narendula, Rammohan; Papaioannou, Thanasis G.; Aberer, Karl

doi:10.1109/icdcsw.2012.62

Cited by 8 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The criteria considered for the selection of a trusted peer from the set of possible candidate heavily affects the availability of data. Indeed, a first proposal was to select at random the peers on which the data are placed [23] from the set of possible candidate trusted replicas. However, replicating data on different random users' devices is not enough to ensure high data availability because peers participating in the network are heterogeneous in terms of demands and online behavior.…”

Section: Replica Selection: Our Proposalmentioning

confidence: 99%

Privacy and Temporal Aware Allocation of Data in Decentralized Online Social Networks

Salve

Guidi

Mori

et al. 2017

Green, Pervasive, and Cloud Computing

View full text Add to dashboard Cite

Distributed Online Social Networks (DOSNs) have recently been proposed to grant users more control over the data they share with the other users. Indeed, in contrast to centralized Online Social Networks (such as Facebook), DOSNs are not based on centralized storage services, because the contents shared by the users are stored on the devices of the users themselves. One of the main challenges in a DOSN comes from guaranteeing availability of the users' contents when the data owner disconnects from the network. In this paper, we focus our attention on data availability by proposing a distributed allocation strategy which takes into account both the privacy policies defined on the contents and the availability patterns (online/offline) of the users in order to allocate their contents on trusted nodes. A linear predictor is used to model and to predict the availability status of the users in a future time interval, on the basis of their past temporal behaviour. We conduct a set of experiments on a set of traces taken from Facebook. The results prove the effectiveness of our approach by showing high availability of users' profiles.

show abstract

Section: Replica Selection: Our Proposalmentioning

confidence: 99%

Privacy and Temporal Aware Allocation of Data in Decentralized Online Social Networks

Salve

Guidi

Mori

et al. 2017

Green, Pervasive, and Cloud Computing

View full text Add to dashboard Cite

show abstract

“…P2P networks provide massive scalability, fault tolerance, privacy, anonymity, and load balancing (see [15] for a survey). We consider a P2P Online Social Network [5,8,21,18], in which users' content is distributed among nodes. Any node in the P2P OSN may initiate a similarity search query.…”

Section: P2p Osn and Canmentioning

confidence: 99%

NearBucket-LSH: Efficient Similarity Search in P2P Networks

Kraus¹,

Carmel

Keidar

et al. 2016

Similarity Search and Applications

View full text Add to dashboard Cite

We present NearBucket-LSH, an effective algorithm for similarity search in large-scale distributed online social networks organized as peer-to-peer overlays. As communication is a dominant consideration in distributed systems, we focus on minimizing the network cost while guaranteeing good search quality. Our algorithm is based on Locality Sensitive Hashing (LSH), which limits the search to collections of objects, called buckets, that have a high probability to be similar to the query. More specifically, NearBucket-LSH employs an LSH extension that searches in near buckets, and improves search quality but also significantly increases the network cost. We decrease the network cost by considering the internals of both LSH and the P2P overlay, and harnessing their properties to our needs. We show that our NearBucket-LSH increases search quality for a given network cost compared to previous art. In many cases, the search quality increases by more than 50%.

show abstract

“…A first proposal was to randomly select the peers on which the data are placed . However, replicating data on different random users' devices is not enough to ensure higher data availability because peers participating in the network are heterogeneous in terms of demands and online behavior.…”

Section: Introductionmentioning

confidence: 99%

“…5 However, replicating data on different random users' devices is not enough to ensure higher data availability because peers participating in the network are heterogeneous in terms of demands and online behavior. 5 However, replicating data on different random users' devices is not enough to ensure higher data availability because peers participating in the network are heterogeneous in terms of demands and online behavior.…”

mentioning

confidence: 99%

Predicting the availability of users' devices in decentralized online social networks

Salve

Guidi

Mori

2017

Concurrency and Computation

View full text Add to dashboard Cite

The understanding of the user temporal behavior is a crucial aspect for all those systems that rely on user resources for daily operations, such as decentralized online social networks (DOSNs).Indeed, DOSNs exploit the devices of their users to take on and share the tasks needed to provide services such as storing the published data. In the last years, the increasing popularity of DOSN services has changed the way of how people interact with each other by enabling users to connect to these services at any time by using their personal devices (such as notebooks or smartphones).As a result, the availability of data in these systems is strongly affected (or reflected) by the temporal behavior of their users in terms of connections to DOSNs. In this paper, we propose the use of linear predictors to address the problem of the availability of user devices and, hence, data in DOSNs. To validate the proposed approaches, we evaluated their performance conducting a set of simulations exploiting a dataset of temporal information concerning the connections to Facebook collected from a set of users. KEYWORDSavailability prediction, decentralized online social networks, user behavior INTRODUCTIONIn the last years, online social networks (OSNs) have proliferated by attracting millions of users that share a large number of contents with each other. According to the International Telecommunication Union (ITU)*, OSNs have reached a global penetration rate of 31%. The evolution of mobile technology (such as smartphones and tablets) is the major driver that makes social networking the most popular online activity, which captures 30% of the time spent by users each day on the Internet † , i.e., about 1 hour and 50 minutes. The most popular OSNs are based on a centralized architecture where the service provider takes control over users' information. However, the centralized structure has several relevant drawbacks. For instance, during the last years, users' privacy in OSNs becomes an ever-increasing concern because private information of the users is exploited by the centralized OSN providers for several purposes. 1,2 Privacy and system scalability are two of the main issues that have led to the decentralization of the social networks.A decentralized online social network (DOSN) 3 is an OSN implemented in a decentralized way (such as peer-to-peer architecture). For instance, Diaspora ‡ and Friendica § are two of the currently available DOSNs that attract more than 669 000 users, and they are based on a network of independent, federated servers that are managed by the users. RetroShare ¶ is another available DOSN that allows users to create friend-to-friend connection for sharing data. In DOSNs, there is no centralized authority since users' devices are exploited to store and manage users' data. For this reason, the decentralization of OSNs requires efficient solutions for dealing with data availability arising when users' devices disconnect from the system. Indeed, the problem of data availability occurs because data of a user should...

show abstract

Towards the Realization of Decentralized Online Social Networks: An Empirical Study

Cited by 8 publications

References 15 publications

Privacy and Temporal Aware Allocation of Data in Decentralized Online Social Networks

Privacy and Temporal Aware Allocation of Data in Decentralized Online Social Networks

NearBucket-LSH: Efficient Similarity Search in P2P Networks

Predicting the availability of users' devices in decentralized online social networks

Contact Info

Product

Resources

About