Smartphone based web browsing wastes a lot of power when downloading webpages due to the special characteristics of the wireless radio interface. In this paper, we identify these special characteristics, and address power consumption issues through two novel techniques. First, we reorganize the computation sequence of the web browser when loading a webpage, so that the web browser can first run the computations that will generate new data transmissions and retrieve these data from the web server. Then, the web browser can put the wireless radio interface into low power state, release the radio resource, and then run the remaining computations. Second, we introduce a practical data mining based method to predict the user reading time of webpages, based on which the smartphone can switch to low power state when the reading time is longer than a threshold. To demonstrate the effectiveness of our energy-aware approaches, we develop a testbed with Android phones on T-Mobile UMTS network. Experimental results show that our approach can reduce the power consumption of smartphone by more than 30 percent during web browsing. Moreover, our solution can further reduce the webpage loading time and increase the network capacity.

Smartphone based web browsing wastes a lot of power when downloading webpages due to the special characteristics of the 3G radio interface. In this paper, we identify these special characteristics, and address power consumption issues through two novel techniques. First, we reorganize the computation sequence of the web browser when loading a webpage, so that the web browser can first run the computations that will generate new data transmissions and retrieve these data from the web server. Then, the web browser can put the 3G radio interface into low power state, release the radio resource, and then run the remaining computations. Second, we introduce a practical data mining based method to predict the user reading time of webpages, based on which the smartphone can switch to low power state when the reading time is longer than a threshold. To demonstrate the effectiveness of our energy-aware approaches, we develop a testbed with Android phones on T-Mobile UMTS network. Experimental results show that our approach can reduce the power consumption of smartphone by more than 30% during web browsing, and reduce the webpage loading time by 17%.

Node mobility and end-to-end disconnections in disruption-tolerant networks (DTNs) greatly impair the effectiveness of data forwarding. Although social-based approaches can address the problem, most existing solutions only focus on forwarding data to a single destination. In this paper, we study multicast with single and multiple data items in DTNs from a social network perspective, develop analytical models for multicast relay selection, and furthermore investigate the essential difference between multicast and unicast in DTNs. The proposed approach selects relays according to their capabilities, measured by social-based metrics, for forwarding data to the destinations. The design of social-based metrics exploits social network concepts such as node centrality and social community, and the selected relays ensure achieving the required data delivery ratio within the given time constraint. Extensive trace-driven simulations show that the proposed approach has similar data delivery ratio and delay to that of Epidemic routing, but significantly reduces data forwarding cost, measured by the number of relays used.

Smart phone is becoming a key element in providing greater user access to the mobile Internet. Many complex applications, which are used to be only on PCs, have been developed and run on smart phones. These applications extend the functionalities of smart phones and make them more convenient for users to be connected. However, they also greatly increase the power consumption of smart phones and many users are frustrated with the long delay of web browsing when using smart phones. In this paper, we have discovered that the key reason of the long delay and high power consumption in web browsing is not due to the bandwidth limitation most of time in 3G networks. The local computation limitation at the smart phone is the real bottleneck for opening most web pages. To address this issue, we propose an architecture, called Virtual-Machine based Proxy (VMP), to shift the computing from smart phones to the VMP. To illustrate the feasibility of deploying the proposed VMP system in 3G networks, we have built a prototype using Xen virtual machines and Android Phones with T-Mobile UMTS network. Experimental results show that compared to normal smart phone browser, our VMP approach reduces the delay by more than 80% and reduces the power consumption during web browsing by more than 45%.

The IP multimedia subsystem (IMS) is being deployed in the third generation (3G) networks since it supports many kinds of multimedia services. However, the security of IMS networks has not been fully examined. This paper presents a novel DoS attack against IMS. By congesting the presence service, a core service of IMS, a malicious attack can cause chained automatic reaction of the system, thus blocking all the services of IMS. Because of the low-volume nature of this attack, an attacker only needs to control several clients to paralyze an IMS network supporting one million users. To address this DoS attack, we propose an online early defense mechanism, which aims to first detect the attack, then identify the malicious clients, and finally block them. We formulate this problem as a change-point detection problem, and solve it based on the non-parametric GRSh test. Through trace-driven experiments, we demonstrate that our defense mechanism can throttle this DoS attack within a short defense time window while generating few false alarms.

Node mobility and end-to-end disconnections in Delay Tolerant Networks (DTNs) greatly impair the effectiveness of data dissemination. Although social-based approaches can be used to address the problem, most existing solutions only focus on forwarding data to a single destination. In this paper, we are the first to study multicast in DTNs from the social network perspective. We study multicast in DTNs with single and multiple data items, investigate the essential difference between multicast and unicast in DTNs, and formulate relay selections for multicast as a unified knapsack problem by exploiting node centrality and social community structures. Extensive trace-driven simulations show that our approach has similar delivery ratio and delay to the Epidemic routing, but can significantly reduce the data forwarding cost measured by the number of relays used.