Suchergebnisse

The privacy paradox describes a phenomenon whereby there is no connection between stated privacy concerns and privacy behaviours. We need to understand the underlying reasons for this paradox if we are to help users to preserve their privacy more effectively. In particular, the Social Networking System (SNS) domain offers a rich area of investigation due to the risks of unwise information disclosure decisions. Our study thus aims to untangle the complicated nature and underlying mechanisms of online privacy-related decisions in SNSs. In this paper, we report on the findings of a Systematic Literature Review (SLR) that revealed a number of factors that are likely to influence online privacy decisions. Our deductive analysis approach was informed by Communicative Privacy Management (CPM) theory. We uncovered a lack of clarity around privacy attitudes and their link to behaviours, which makes it challenging to design privacy-protecting SNS platforms and to craft legislation to ensure that users' privacy is preserved.

In wireless communication environments, backoff is traditionally based on the IEEE binary exponential backoff (BEB). Using BEB results in a high delay in message transmission, collisions, and ultimately wasting the limited available bandwidth. As each node has to obtain medium access before transmitting a message, in dense networks, the collision probability in the medium access control (MAC) layer becomes very high, when a poor backoff algorithm is used. The logarithmic algorithm proposes some improvements to the backoff algorithms that aim to efficiently use the channel and to reduce collisions. The algorithm under study is based on changing the incremental behavior of the backoff value. The BEB is used by the local area networks (LANs) standards, IEEE 802.11, MAC. BEB uses a uniform random distribution to choose the backoff value; this often leads to reducing the effect of a window-sized increment. This paper carries out a deeper study and analysis of the logarithmic backoff algorithm that uses logarithmic increments, instead of an exponential extension of the window size to eliminate the degrading effect of random number distribution. Results from simulation experiments reveal that the algorithm subject under study achieves higher throughput and less packet loss, when in a mobile ad hoc environment.