Showing papers presented at "IFIP Wireless Days in 2017"

ARMA based popularity prediction for caching in Content Delivery Networks

Abstract: Content Delivery Networks (CDNs) are faced with an increasing and time varying demand of video contents. Their ability to promptly react to this demand is a success factor. Caching helps, but the question is: which contents to cache? Considering that the most popular contents should be cached, this paper focuses on how to predict the popularity of video contents. With real traces extracted from YouTube, we show that Auto-Regressive and Moving Average (ARMA) models can provide accurate predictions. We propose an original solution combining the predictions of several ARMA models. This solution achieves a better Hit Ratio and a smaller Update Ratio than the classical Least Frequently Used (LFU) caching technique.

Node ranking in wireless sensor networks with linear topology

Abstract: In wireless sensor networks with linear topology, knowing the physical order in which nodes are deployed is useful not only for the target application, but also to some network services, like routing or data aggregation. Considering the limited resources of sensor nodes, the design of autonomous protocols to find this order is a challenging topic. In this paper, we propose a distributed and iterative centroid-based algorithm to address this problem. At each iteration, the algorithm selects two virtual anchors and finds the order of a subset of nodes, placed between these two anchors. The proposed algorithm requires local node connectivity knowledge and the identifier of the first sensor node of the network, which is the only manually configured parameter. This solution, scalable and lightweight from the deployment and maintenance point of view, is shown to be robust to connectivity degradation, correctly ordering more than 95% of the nodes, even under very low connectivity conditions

2.4 GHz single anchor node indoor localization system with angle of arrival fingerprinting

Abstract: Location prevails as a piece of crucial information for decision-making processes. Whereas positioning in outdoor environments can be mainly attributed to Global Navigation Satellite Systems, no single technology can be appointed for accurate indoor localization. Many approaches exist, mostly relying on line-of-sight propagation from a mobile node to multiple anchor nodes. These solutions not only require complex installations, but in many cases they also make inapplicable assumptions about indoor environments. This paper investigates an indoor localization system with a single anchor node, estimating the position of an omnidirectional mobile transmitter by fingerprinting angle of arrival data. Measurements were taken with a 10-elements uniform linear antenna array at a 2.47 GHz carrier frequency. Three different scenarios were defined for the evaluation of localization errors and the influence of spatial smoothing, a technique for signal decorrelation.

A greedy approach for resource allocation in Virtual Sensor Networks

Abstract: Virtual Sensor Networks (VSNs) envision the creation of general purpose wireless sensor networks which can be easily adapted and configured to support multifold applications with heterogeneous requirements, in contrast with the classical approach of wireless sensor networks vertically optimized on one specific task/service. The very heart of VSNs' vision is the capability to dynamically allocate shared physical resources (processing power, bandwidth, storage) to multiple incoming applications. In this context, we tackle the problem of optimally allocating shared resources in VSNs by proposing an efficient greedy heuristic that aims to maximize the total revenue out of the deployment of multiple concurrent applications while considering the inherent limitations of the shared physical resources. The proposed heuristic is tested on realistic network instances with notable performances in terms of execution time while keeping the gap with respect to the optimal solution limited (below 5% in the tested environments).

Software Defined Networking to support IP address mobility in future LTE network

Abstract: The existing LTE network architecture dose not scale well to increasing demands due to its highly centralized and hierarchical composition. In this paper we discuss the major modifications required in the current LTE network to realize a decentralized LTE architecture. Next, we develop two IP address mobility support schemes for this architecture. The proposed solutions can handle traffic redirecting and seamless IP address continuity for the nodes moving among the distributed anchor points in a resource efficient manner. Our approaches are based on the SDN (Software Defined Networking) paradigm which is also one of the most important candidate technologies to realize 5G mobile networks. We extend the NS3-LENA simulation software to implement a decentralized LTE network as well as the proposed IP mobility support schemes. The evaluation results show that the proposed solutions efficiently fulfill the functionality and performance requirements (e.g., latency and packet loss) related to mobility management.

Data Freshness Aware Content-Centric Networking in WSNs

Abstract: The Content-Centric Networking (CCN) concept is a significant approach of several future Internet research activities. CCN in Wireless Sensor Networks present a promised technique that may ensure data routing based on content. In this paper, we focus on the lifetime of the Content Object exchanged in the network and we explain the idea of its integration in CCN for WSNs to better highlight the relevance of its exploitation. To this end, we implement DFCCN-WSNs ‘Data Freshness aware Content-Centric Networking in Wireless Sensor Networks’ a protocol that implements the data lifetime. Through extensive simulations, we demonstrate that DFCCN-WSNs outperforms traditional CCN in terms of end-to-end delay.