Emerging information-centric networking architectures seek to optimally utilize both bandwidth and storage for efficient content distribution. This highlights the need joint design of traffic engineering caching strategies, in order optimize network performance view current loads future demands. We present a systematic framework dynamic interest request forwarding cache placement eviction, within context Named Data Networking (NDN) architecture. The employs virtual control plane which...

Context-aware mobile computing requires wearable sensors to acquire information about the user. Continuous sensing rapidly depletes -wearable system's energy, which is a critically constrained resource. In this paper, we analyze trade-off between power consumption and prediction accuracy of context classifiers working on dual-axis accelerometer data collected from eWaich notification platform. We improve techniques by providing competitive classification performance even in low frequency...

We examine the problem of allocating a given total storage budget in distributed system for maximum reliability. A source has single data object that is to be coded and stored over set nodes; it allowed store any amount each node, as long used does not exceed budget. collector subsequently attempts recover original by accessing only random subset nodes. By using an appropriate code, successful recovery can achieved whenever accessed at least size object. The goal find optimal allocation...

Mobile crowdsensing has emerged as an efficient sensing paradigm that combines the crowd intelligence and power of mobile devices, such phones Internet Things gadgets. This article addresses contradicting incentives privacy preservation by users, accuracy maximization collection true data service providers. We first define individual contributions users based on in analytics achieved provider from buying their data. then propose a truthful mechanism for achieving high while protecting user...

We consider a real-time streaming system where messages are created sequentially at the source, and encoded for transmission over packet erasure channel. Each message must subsequently be decoded receiver within given delay from its creation time. code design maximum rates when all decodable by their respective deadlines under specified set of patterns (erasure model). Specifically, we provide construction that achieves optimal rate an asymptotic number messages, models containing limited...

We consider a real-time streaming system where messages created at regular time intervals source are encoded for transmission to receiver over packet erasure link; the must subsequently decode each message within given delay from its creation time. study bursty model in which all patterns containing bursts of limited length admissible. For certain classes parameter values, we provide code constructions that asymptotically achieve maximum size among codes allow decoding under admissible...

We develop a new location spoofing detection algorithm for geo-spatial tagging and location-based services in the Internet of Things (IoT), called enhanced using audibility (ELSA), which can be implemented at backend server without modifying existing legacy IoT systems. ELSA is based on statistical decision theory framework uses two-way time-of-arrival (TW-TOA) information between user's device anchors. In addition to TW-TOA information, exploits implicit (or outage information) improve...

Internet of things (IoT) produces massive data from devices embedded with sensors. The IoT allows creating profitable services using machine learning. However, previous research does not address the problem optimal pricing and bundling learning-based services. In this paper, we define value service quality a learning perspective. We present an market model which consists vendors selling to providers, providers offering customers. Then, introduce schemes for standalone bundled sales, provider...

We consider the problem of optimally allocating a given total storage budget in distributed system. A source has data object which it can code and store over set nodes; is allowed to any amount each node, subject constraint. collector subsequently attempts recover original by accessing random fixed-size subset these nodes. Successful recovery occurs when coded this nodes at least size object. The goal determine node so that probability successful maximized. solve high regime. Our results be...

Privacy-preserving routing protocols in wireless networks frequently utilize additional artificial traffic to hide the identities of communicating source-destination pairs. Usually, addition is done heuristically with no guarantees that transmission cost, latency, and so on, are optimized every network topology. In this paper, we explicitly examine privacy-utility tradeoff problem for develop a novel privacy-preserving algorithm called optimal privacy enhancing (OPERA). OPERA uses...

With the emerging sensing technologies such as mobile crowdsensing and Internet of Things (IoT), people-centric data can be efficiently collected used for analytics optimization purposes. This is typically required to develop render services. In this paper, we address privacy implication, optimal pricing, bundling We first define inverse correlation between service quality level from perspectives. then present profit maximization models selling standalone, complementary, substitute...

Time synchronization is an enabling service that allows devices to share a consistent notion of time and thus makes it easier build efficient robust collaborative services. However, existing protocols based on wireless packet transmissions are not energy because powering the radio often consumes significant fraction budget. In this paper, we propose PSync, visible light-based protocol relies LED light source highly for receivers. The key novelty in our use De Bruijn sequence provide rough...

We investigate the problem of using several storage nodes to store a data object, subject an aggregate budget or redundancy constraint. It is challenging find optimal allocation that maximizes probability successful recovery by collector because large space possible symmetric and nonsymmetric allocations, nonconvexity problem. For special case probability-1 recovery, we show minimizes required symmetric. further explore access models, determine in high-probability regime for interest. Based...

We consider the problem of optimally allocating a given total storage budget in distributed system. A source has data object which it can code and store over set nodes; is allowed to any amount coded each node, as long used does not exceed budget. collector subsequently attempts recover original by accessing nodes independently with some constant probability. By using an appropriate code, successful recovery occurs when accessed at least size object. The goal find optimal allocation that...

We examine the problem of creating an encoded distributed storage representation a data object for network mobile nodes so as to achieve optimal recovery delay. A source node creates single and disseminates it other storage, subject given total budget. collector subsequently attempts recover original by contacting accessing stored in them. By using appropriate code, successful is achieved when amount accessed at least size object. The goal find allocation budget over that optimizes delay...

In deploying body sensor networks (BSNs), sampling rates might be dynamically tuned to fit application requirements (e.g., monitoring patients' different activities), which helps conserving energy for battery-powered sensors. However, this results in variable data among sensors, further requires an efficient resource allocation maintain reliable transmission accommodating all traffic loads. We thereby address joint problem of reliability and efficiency by proposing a BSN system that...

Emerging information-centric networking architectures seek to optimally utilize both bandwidth and storage for efficient content distribution. This highlights the need joint design of traffic engineering caching strategies. We present a systematic framework dynamic interest request forwarding cache placement eviction, within context Named Data Networking (NDN) architecture. The employs virtual control plane which operates on user demand rate data objects in network, an actual handles...

We present a unified linear program formulation for optimal content delivery in networks (CDNs), taking into account various costs and constraints associated with dissemination from the origin server to storage nodes, data storage, eventual fetching of nodes by end users. Our can be used achieve variety performance goals system behavior, including bounding fetch delay, load balancing, robustness against node arc failures. Simulation results suggest that our performs significantly better than...

We consider a distributed storage system where the nodes have heterogeneous access probabilities. The problem is to allocate given budget across so as store unit-size data object with maximum reliability. propose efficient algorithms for optimizing over several classes of allocations. In basic one-level symmetric allocation, spread evenly an appropriately chosen subset nodes. multi k-level divided into k parts, each different nodes, such that amount allocated node in higher levels multiple...

We propose a new framework combining dynamic sampling rates for healthcare sensors driven by user behavior, and an adaptive MAC scheduling scheme applied to the time-slotted channel hopping (TSCH) protocol in IEEE 802.15.4, which provides high throughput reliable communications. First, we introduce system software architecture machine-learning-assisted monitoring that detects user's behavior using edge computing adjusts of accordingly. Second, TSCH based on state machine model reacts traffic...

We present a phantom-receiver-based routing scheme to enhance the anonymity of each source-destination pair (or contextual privacy) while using an adjustable amount overhead. also study how traditional network coding and opportunistic can leak privacy. then incorporated both into our for better performance show we mitigate its vulnerability. Contrary prior works, allow destination anonymously submit acknowledgment source enhanced reliability. Performance analysis simulations are used...

Mobile crowd sensing is an emerging paradigm where applications buy sensor data from mobile smartphone users (workers) instead of deploying their own networks to estimate some statistics a spatial event. In many monitoring applications, the crowdsourcer needs incentivize contribute so that collected dataset has good coverage. To further privacy-concerned workers contribute, we propose Stackelberg incentive framework allows specify location privacy requirements while also increasing coverage...