Performance modelling of opportunistic forwarding under heterogenous mobility

The Delay Tolerant Networking paradigm aims to enable communications in disconnected environments where traditional protocols would fail. Oppor- tunistic networks are delay tolerant networks whose nodes are typically the users\u27 personal mobile devices. Communications in an opportunistic network rely on the mobility of users: each message is forwarded from node to node, according to a hop-by-hop decision process that selects the node that is better suited for bringing the message closer to its destination. Despite the variety of forwarding protocols that have been proposed in the recent years, there is no reference framework for the performance modelling of opportunistic for- warding. In this paper we start to ll this gap by proposing an analytical model for the rst two moments of the delay and the number of hops expe- rienced by messages when delivered in an opportunistic fashion. This model seamlessly integrates both social-aware and social-oblivious single-copy for- warding protocols, as well as dierent hypotheses for user contact dynamics. More specically, the model can be solved exactly in the case of exponential and Pareto inter-meeting times, two popular cases emerged from the liter- ature on human mobility analysis. In order to exemplify how the proposed framework can be used, we discuss its application to two case studies with dierent mobility settings. Finally, we discuss how the framework can be also solved exactly when inter-meeting times follow a hyper-exponential distribu- tion. This case is particularly relevant as hyper-exponential distributions are able to approximate the large class of high-variance distributions (distribu- tions with coecient of variation greater than one), which are those more challenging, e.g., from the delay standpoint

V-Edge: Virtual Edge Computing as an Enabler for Novel Microservices and Cooperative Computing

As we move from 5G to 6G, edge computing is one of the concepts that needs revisiting. Its core idea is still intriguing: instead of sending all data and tasks from an end user's device to the cloud, possibly covering thousands of kilometers and introducing delays that are just owed to limited propagation speed, edge servers deployed in close proximity to the user, e.g., at some 5G gNB, serve as proxy for the cloud. Yet this promising idea is hampered by the limited availability of such edge servers. In this paper, we discuss a way forward, namely the virtual edge computing (V-Edge) concept. V-Edge bridges the gap between cloud, edge, and fog by virtualizing all available resources including the end users' devices and making these resources widely available using well-defined interfaces. V-Edge also acts as an enabler for novel microservices as well as cooperative computing solutions. We introduce the general V-Edge architecture and we characterize some of the key research challenges to overcome, in order to enable wide-spread and even more powerful edge services

Two birds, one stone : using mobility behavioral profiles both as destinations and as a routing tool

We present HabCast, a profile-cast communication paradigm that learns about the mobility habits of the location-aware nodes of the network and uses this information both to route the messages, and to deliver them only to the nodes that match the target behavioral profile. HabCast substitutes destination's identifier by a mobility profile model called habitat, meaning that allows users to send messages "to any nodes who usually roams around this area" instead of sending messages intended to a node. HabCast is designed to operate without network infrastructure, using Opportunistic Networking strategies and operates in three phases: approximation, floating and delivery phase. HabCast enables new services and applications on Opportunistic Networking by automatically inferring the nodes' behavioral profiles and using them to define the messages' destinations. The overhead introduced by HabCast is evaluated using a proof-of-concept implementation, and its performance and feasibility is studied, through simulation, under the scope of a real carsharing application

Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

A novel queue management policy for delay-tolerant networks

Delay-tolerant networks (DTNs) have attracted increasing attention from governments, academia and industries in recent years. They are designed to provide a communication channel that exploits the inherent mobility of trams, buses and cars. However, the resulting highly dynamic network suffers from frequent disconnections, thereby making node-to-node communications extremely challenging. Researchers have thus proposed many routing/forwarding strategies in order to achieve high delivery ratios and/or low latencies and/or low overheads. Their main idea is to have nodes store and carry information bundles until a forwarding opportunity arises. This, however, creates the following problems. Nodes may have short contacts and/or insufficient buffer space. Consequently, nodes need to determine (i) the delivery order of bundles at each forwarding opportunity and (ii) the bundles that should be dropped when their buffer is full. To this end, we propose an efficient scheduling and drop policy for use under quota-based protocols. In particular, we make use of the encounter rate of nodes and context information such as time to live, number of available replicas and maximum number of forwarded bundle replicas to derive a bundle\u27s priority. Simulation results, over a service quality metric comprising of delivery, delay and overhead, show that the proposed policy achieves up to 80 % improvement when nodes have an infinite buffer and up to 35 % when nodes have a finite buffer over six popular queuing policies: Drop Oldest (DO), Last Input First Output (LIFO), First Input First Output (FIFO), Most FOrwarded first (MOFO), LEast PRobable first (LEPR) and drop bundles with the greatest hop-count (HOP-COUNT)

Performance modelling of opportunistic forwarding with exact knowledge

The Delay Tolerant Networking paradigm aims to enable communications in disconnected environments where traditional protocols would fail. Opportunistic networks are delay tolerant networks whose nodes are typically the users\u27 personal mobile devices. Communications in an opportunistic network rely on the mobility of users: each message is forwarded from node to node, according to a hop-by-hop decision process that selects the node that is better suited for bringing the message closer to its destination. Despite the variety of forwarding protocols that have been proposed in the recent years, there is no reference framework for the performance modelling of opportunistic forwarding. In this paper we start to fill this gap by proposing an analytical model for the expected delay and the expected number of hops experienced by messages when delivered in an opportunistic fashion. This model seamlessly integrates both social-aware and social-oblivious single-copy forwarding protocols, as well as different hypotheses for user contact dynamics. The proposed framework is used to derive bounds on the expected delay under homogeneous and heterogeneous contact patterns. We found that, in heterogeneous settings, finite expected delay can be guaranteed not only when nodes\u27 inter-meeting times follow an exponential or power law with exponential cut-off distribution, but also when they are power law distributed, as long as weaker conditions than those derived by Chaintreau et al. [1] for the homogeneous scenario are satisfied

L-CAQ: Joint link-oriented channel-availability and channel-quality based channel selection for mobile cognitive radio networks

Channel availability probability (CAP) and channel quality (CQ) are two key metrics that can be used to efficiently design a channel selection strategy in cognitive radio networks. For static scenarios, i.e., where all the users are immobile, the CAP metric depends only on the primary users' activity whereas the CQ metric remains relatively constant. In contrast, for mobile scenarios, the values of both metrics fluctuate not only with time (time-variant) but also over different links between users (link-variant) due to the dynamic variation of primary- and secondary-users' relative positions. As an attempt to address this dynamic fluctuation, this paper proposes L-CAQ: a link-oriented channel-availability and channel-quality based channel selection strategy that aims to maximize the link throughput. The L-CAQ scheme considers accurate estimation of the aforementioned two channel selection metrics, which are governed by the mobility-induced non-stationary network topology, and endeavors to select a channel that jointly maximizes the CAP and CQ. The benefits of the proposed scheme are demonstrated through numerical simulation for mobile cognitive radio networks