The cloud seems to be an excellent companion of mobile systems, to alleviate battery consumption on smartphones and to backup user's data on-the-fly. Indeed, many recent works focus on frameworks that enable mobile computation offloading to software clones of smartphones on the cloud and on designing cloud-based backup systems for the data stored in our devices. Both mobile computation offloading and data backup involve communication between the real devices and the cloud. This communication does certainly not come for free. It costs in terms of bandwidth (the traffic overhead to communicate with the cloud) and in terms of energy (computation and use of network interfaces on the device).In this work we study the feasibility of both mobile computation offloading and mobile software/data backups in real-life scenarios. In our study we assume an architecture where each real device is associated to a software clone on the cloud. We consider two types of clones: The off-clone, whose purpose is to support computation offloading, and the back-clone, which comes to use when a restore of user's data and apps is needed. We give a precise evaluation of the feasibility and costs of both off-clones and back-clones in terms of bandwidth and energy consumption on the real device. We achieve this through measurements done on a real testbed of 11 Android smartphones and an equal number of software clones running on the Amazon EC2 public cloud. The smartphones have been used as the primary mobile by the participants for the whole experiment duration. I. INTRODUCTIONThe advances in technology of the last decades have undoubtedly turned yesterday's must-have devices into today's stock. Think of the phones with aerials of the late '80, or the Pentium 4 PCs of a few years ago. None of them is comparable to the power of nowadays smartphones, whose recent worldwide market boost is undeniable. We use smartphones to do many of the jobs we used to do on desktops, and many new ones. We browse the Internet, send emails, organize our lives, watch videos, upload data on social networks, use online banking, find our way by using GPS and online maps, and communicate in revolutionary ways. New apps are coming out at an incredible pace. Apple iPhone commercial's call to action "There's an app for everything" says a lot on this Alessandro Mei is supported by a Marie Curie Outgoing International Fellowship funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n. 253461. This work has been technically supported and partially funded by Telecom Italia within the Working Capital project.This work has been performed in the framework of the FP7 project TROPIC IST-318784 STP, which is funded by the European Community. The Authors would like to acknowledge the contributions of their colleagues from TROPIC Consortium (http://www.ict-tropic.eu).
Wireless sensor networks are often deployed in hostile environments, where anadversary can physically capture some of the nodes. Once a node is captured, the attackercan re-program it and replicate the node in a large number of clones, thus easily taking over the network. The detection of node replication attacks in a wireless sensor network is therefore a fundamental problem. A few distributed solutions have recently been proposed. However, these solutions are not satisfactory. First, they are energy and memory demanding: A serious drawback for any protocol that is to be used in resource constrained environment such as a sensor network. Further, they are vulnerable to specific adversary models introduced in this paper. The contributions of this work are threefold. First, we analyze the desirable properties of a distributed mechanism for the detection of node replication attacks. Second, we show that the known solutions for this problem do not completely meet our requirements. Third, we propose a new Randomized, Efficient, and Distributed (RED) protocol for the detection of node replication attacks and we show that it is completely satisfactory with respect to the requirements. Extensive simulations also show that our protocol is highly efficient in communication, memory, and computation, that it sets out an improved attack detection probability compared to the best solutions in the literature, and that it is resistant to the new kind of attacks we introduce in this paper, while other solutions are not. Copyright 2007 ACM
Abstract-In this paper we describe SANE, the first forwarding mechanism that combines the advantages of both social-aware and stateless approaches in pocket switched network routing. SANE is based on the observation-that we validate on realworld traces-that individuals with similar interests tend to meet more often. In our approach, individuals (network members) are characterized by their interest profile, a compact representation of their interests. Through extensive experiments, we show the superiority of social-aware, stateless forwarding over existing stateful, social-aware and stateless, social-oblivious forwarding. An important byproduct of our interest-based approach is that it easily enables innovative routing primitives, such as interestcasting. An interest-casting protocol is also described, and extensively evaluated through experiments based on both real-world and synthetic mobility traces.
Wireless Sensor Networks (WSNs) are often deployed in hostile environments where an adversary can physically capture some of the nodes, first can reprogram, and then, can replicate them in a large number of clones, easily taking control over the network. A few distributed solutions to address this fundamental problem have been recently proposed. However, these solutions are not satisfactory. First, they are energy and memory demanding: A serious drawback for any protocol to be used in the WSN-resource-constrained environment. Further, they are vulnerable to the specific adversary models introduced in this paper. The contributions of this work are threefold. First, we analyze the desirable properties of a distributed mechanism for the detection of node replication attacks. Second, we show that the known solutions for this problem do not completely meet our requirements. Third, we propose a new self-healing, Randomized, Efficient, and Distributed (RED) protocol for the detection of node replication attacks, and we show that it satisfies the introduced requirements. Finally, extensive simulations show that our protocol is highly efficient in communication, memory, and computation; is much more effective than competing solutions in the literature; and is resistant to the new kind of attacks introduced in this paper, while other solutions are not
We give, for the first time, a precise mathematical analysis of the connectivity and security proper-\ud ties of sensor networks that make use of the random predistribution of keys. We also show how to\ud set the parameters—pool and key ring size—in such a way that the network is not only connected\ud with high probability via secure links but also provably resilient, in the following sense: We for-\ud mally show that any adversary that captures sensors at random with the aim of compromising\ud a constant fraction of the secure links must capture at least a constant fraction of the nodes of\ud the network. In the context of wireless sensor networks where random predistribution of keys is\ud employed, we are the first to provide a mathematically precise proof, with a clear indication of\ud parameter choice, that two crucial properties—connectivity via secure links and resilience against\ud malicious attacks—can be obtained simultaneously. We also show in a mathematically rigorous\ud way that the network enjoys another strong security property. The adversary cannot partition\ud the network into two linear size components, compromising all the links between them, unless it\ud captures linearly many nodes. This implies that the network is also fault tolerant with respect to\ud node failures. Our theoretical results are complemented by extensive simulations that reinforce\ud our main conclusions
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