Forever Young: Aging Control For Smartphones In Hybrid Networks

The demand for Internet services that require frequent updates through small messages, such as microblogging, has tremendously grown in the past few years. Although the use of such applications by domestic users is usually free, their access from mobile devices is subject to fees and consumes energy from limited batteries. If a user activates his mobile device and is in range of a service provider, a content update is received at the expense of monetary and energy costs. Thus, users face a tradeoff between such costs and their messages aging. The goal of this paper is to show how to cope with such a tradeoff, by devising \emph{aging control policies}. An aging control policy consists of deciding, based on the current utility of the last message received, whether to activate the mobile device, and if so, which technology to use (WiFi or 3G). We present a model that yields the optimal aging control policy. Our model is based on a Markov Decision Process in which states correspond to message ages. Using our model, we show the existence of an optimal strategy in the class of threshold strategies, wherein users activate their mobile devices if the age of their messages surpasses a given threshold and remain inactive otherwise. We then consider strategic content providers (publishers) that offer \emph{bonus packages} to users, so as to incent them to download updates of advertisement campaigns. We provide simple algorithms for publishers to determine optimal bonus levels, leveraging the fact that users adopt their optimal aging control strategies. The accuracy of our model is validated against traces from the UMass DieselNet bus network.Comment: See also http://www-net.cs.umass.edu/~sadoc/agecontrol

Collaborative Uploading in Heterogeneous Networks: Optimal and Adaptive Strategies

Collaborative uploading describes a type of crowdsourcing scenario in networked environments where a device utilizes multiple paths over neighboring devices to upload content to a centralized processing entity such as a cloud service. Intermediate devices may aggregate and preprocess this data stream. Such scenarios arise in the composition and aggregation of information, e.g., from smartphones or sensors. We use a queuing theoretic description of the collaborative uploading scenario, capturing the ability to split data into chunks that are then transmitted over multiple paths, and finally merged at the destination. We analyze replication and allocation strategies that control the mapping of data to paths and provide closed-form expressions that pinpoint the optimal strategy given a description of the paths' service distributions. Finally, we provide an online path-aware adaptation of the allocation strategy that uses statistical inference to sequentially minimize the expected waiting time for the uploaded data. Numerical results show the effectiveness of the adaptive approach compared to the proportional allocation and a variant of the join-the-shortest-queue allocation, especially for bursty path conditions.Comment: 15 pages, 11 figures, extended version of a conference paper accepted for publication in the Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), 201

Distribuirani obrambeni mehanizmi za clone napade temeljeni na algoritmu za istraživanje gravitacije (GSA) u WSN

Wireless Sensor Networks (WSN) are often deployed in hostile environment and are vulnerable to attacks because of the resource constrained nature of the sensors. Clone attack in WSN is one of the major issues where the messages are eavesdropped, the captured node is cloned, and multiple nodes with same identity are produced by attacker. In order to overcome these issues, in this paper, a Distributed Defense Mechanism for Clone Attacks based on Gravitational Search Algorithm (GSA) in WSN is proposed. For efficiently detecting the suspect nodes, the nodes in the channel can be divided into witness node and the claimer node. The witness nodes are responsible for the suspect nodes detection, whereas the claimer nodes should provide their identities for the detection process. For the witness nodes selection, we utilize the GSA to pick out the best witness nodes set. After selecting the witness nodes, clone attack detection is performed by observing the behavior of the neighbor nodes. On detecting the clone attack, revocation procedure is triggered to revoke the clone attack in the witness nodes. By simulation results, it can be concluded that the proposed algorithm provides better protection to clone attacks by reducing the packet drop and increasing the packet delivery ratio.Bežične senzorske mreže (WSN) često su raspoređene u neprijateljskom okruženju i ranjive su na napade zbog prirode senzora koji su tehnološki ograničeni. Clone napad u WSN jedan je od glavnih problema gdje se poruke prisluškuju, zarobljeni čvor se klonira te napadač proizvede višestruke čvorove istog identiteta. Kako bi nadvladali te probleme, ovaj rad predlaže distribuirani obrambeni mehanizam za clone napade temeljen na algoritmu za istraživanje gravitacije (GSA) u WSN. Kako bi se sumnjivi čvorovi efikasno detektirali, čvorovi u kanalu mogu se podijeliti u čvorove svjedoke i tražene čvorove. Čvorovi svjedoci odgovorni su za otkrivanje sumnjivih čvorova, dok traženi čvorovi trebaju za potrebe procesa detekcije navesti svoj identitet. Za izbor čvorova svjedoka, koristi se GSA kako bi se izabrala grupa čvorova koji su najprikladniji. Nakon izbora čvorova svjedoka, otkivanje clone napada vrši se promatranjem ponašanja susjednih čvorova. Otkrivanjem clone napada aktivira se proces opoziva kako bi se opozvao clone napad u čvorovima svjedocima. Prema rezultatima dobivenim iz simulacije može se zaključiti kako predloženi algoritam pruža bolju zaštitu od clone napada smanjivanjem odbacivanja paketa i povećavanjem omjera isporuke paketa

Adaptive real-time predictive collaborative content discovery and retrieval in mobile disconnection prone networks

Emerging mobile environments motivate the need for the development of new distributed technologies which are able to support dynamic peer to peer content sharing, decrease high operating costs, and handle intermittent disconnections. In this paper, we investigate complex challenges related to the mobile disconnection tolerant discovery of content that may be stored in mobile devices and its delivery to the requesting nodes in mobile resource-constrained heterogeneous environments. We propose a new adaptive real-time predictive multi-layer caching and forwarding approach, CafRepCache, which is collaborative, resource, latency, and content aware. CafRepCache comprises multiple multi-layer complementary real-time distributed predictive heuristics which allow it to respond and adapt to time-varying network topology, dynamically changing resources, and workloads while managing complex dynamic tradeoffs between them in real time. We extensively evaluate our work against three competitive protocols across a range of metrics over three heterogeneous real-world mobility traces in the face of vastly different workloads and content popularity patterns. We show that CafRepCache consistently maintains higher cache availability, efficiency and success ratios while keeping lower delays, packet loss rates, and caching footprint compared to the three competing protocols across three traces when dynamically varying content popularity and dynamic mobility of content publishers and subscribers. We also show that the computational cost and network overheads of CafRepCache are only marginally increased compared with the other competing protocols

Network and Energy-Aware Resource Selection Model for Opportunistic Grids

Due to increasing hardware capacity, computing grids have been handling and processing more data. This has led to higher amount of energy being consumed by grids; hence the necessity for strategies to reduce their energy consumption. Scheduling is a process carried out to define in which node tasks will be executed in the grid. This process can significantly impact the global system performance, including energy consumption. This paper focuses on a scheduling model for opportunistic grids that considers network traffic, distance between input files and execution node as well as the execution node status. The model was tested in a simulated environment created using GreenCloud. The simulation results of this model compared to a usual approach show a total power consumption savings of 7.10%

Towards Trustworthy, Efficient and Scalable Distributed Wireless Systems

Advances in wireless technologies have enabled distributed mobile devices to connect with each other to form distributed wireless systems. Due to the absence of infrastructure, distributed wireless systems require node cooperation in multi-hop routing. However, the openness and decentralized nature of distributed wireless systems where each node labors under a resource constraint introduces three challenges: (1) cooperation incentives that effectively encourage nodes to offer services and thwart the intentions of selfish and malicious nodes, (2) cooperation incentives that are efficient to deploy, use and maintain, and (3) routing to efficiently deliver messages with less overhead and lower delay. While most previous cooperation incentive mechanisms rely on either a reputation system or a price system, neither provides sufficiently effective cooperation incentives nor efficient resource consumption. Also, previous routing algorithms are not sufficiently efficient in terms of routing overhead or delay. In this research, we propose mechanisms to improve the trustworthiness, scalability, and efficiency of the distributed wireless systems. Regarding trustworthiness, we study previous cooperation incentives based on game theory models. We then propose an integrated system that combines a reputation system and a price system to leverage the advantages of both methods to provide trustworthy services. Analytical and simulation results show higher performance for the integrated system compared to the other two systems in terms of the effectiveness of the cooperation incentives and detection of selfish nodes. Regarding scalability in a large-scale system, we propose a hierarchical Account-aided Reputation Management system (ARM) to efficiently and effectively provide cooperation incentives with small overhead. To globally collect all node reputation information to accurately calculate node reputation information and detect abnormal reputation information with low overhead, ARM builds a hierarchical locality-aware Distributed Hash Table (DHT) infrastructure for the efficient and integrated operation of both reputation systems and price systems. Based on the DHT infrastructure, ARM can reduce the reputation management overhead in reputation and price systems. We also design a distributed reputation manager auditing protocol to detect a malicious reputation manager. The experimental results show that ARM can detect the uncooperative nodes that gain fraudulent benefits while still being considered as trustworthy in previous reputation and price systems. Also, it can effectively identify misreported, falsified, and conspiratorial information, providing accurate node reputations that truly reflect node behaviors. Regarding an efficient distributed system, we propose a social network and duration utility-based distributed multi-copy routing protocol for delay tolerant networks based on the ARM system. The routing protocol fully exploits node movement patterns in the social network to increase delivery throughput and decrease delivery delay while generating low overhead. The simulation results show that the proposed routing protocol outperforms the epidemic routing and spray and wait routing in terms of higher message delivery throughput, lower message delivery delay, lower message delivery overhead, and higher packet delivery success rate. The three components proposed in this dissertation research improve the trustworthiness, scalability, and efficiency of distributed wireless systems to meet the requirements of diversified distributed wireless applications