Communication is the most common but an intricate activity that we perform every day. Sender sends message, discussions, greetings, gestures, emotics and texts through numerous channels, (e.g. e-mail, messengers, social networks and so on) intending the receiver to understand. The means of personal or group communication has been radically changed over last decade. Geographical, ethnicity, nationality, race, religion are no more hindrance for the sake of social communication. Forms of communication, event, gathering, greetings almost have altered into virtual society. But this hi-tech society has still yet enough room to strengthen its semantic nature. We have made an endeavor to conglomerate the socio-psycho-technical aspect of so-called social networks which could be more realistic, logically inferable and convincible towards people to claim its analogousness with real society. Our devised SN is able to eliminate some weird problems that we face in current SNs, imperfect relationship assignment policies and possibility of data interference among desired and intruder groups.

In this paper, a wavelet-based progressive image transmission (PIT) scheme is proposed. Here a combined method is proposed to reduce the image browsing time. The proposed scheme transforms a digital image from spatial domain into frequency domain by using discrete wavelet transformation. For wavelet transformation phase we have used Haar wavelet transformation. But it is computationally rigorous. Using concurrent computing we have significantly reduced computation time overhead as well as transmission time. According to the experimental results, the proposed scheme provides the accuracy of reconstructed image and the image browsing time reduces significantly.