Infective flooding in low-duty-cycle networks, properties and bounds

Flooding information is an important function in many networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the distributed computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient resource allocation to flood information in mesh networks with low duty-cycling without the need to build a distribution tree or any other distribution overlay. Furthermore, the method requires only local computations based on each node neighborhood. The model provides lower and upper stochastic bounds on the flooding delay averages on all possible sources with high probability. We show that the lower bound is very close to the theoretical optimum. A simulation-based implementation allows the study of specific topologies and graph models as well as scheduling heuristics and packet losses. Simulation experiments show that simple protocols based on our resource allocation strategy can easily achieve results that are very close to the theoretical minimum obtained building optimized overlays on the network

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

PiCasso: enabling information-centric multi-tenancy at the edge of community mesh networks

© 2019 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Edge computing is radically shaping the way Internet services are run by enabling computations to be available close to the users - thus mitigating the latency and performance challenges faced in today’s Internet infrastructure. Emerging markets, rural and remote communities are further away from the cloud and edge computing has indeed become an essential panacea. Many solutions have been recently proposed to facilitate efficient service delivery in edge data centers. However, we argue that those solutions cannot fully support the operations in Community Mesh Networks (CMNs) since the network connection may be less reliable and exhibit variable performance. In this paper, we propose to leverage lightweight virtualisation, Information-Centric Networking (ICN), and service deployment algorithms to overcome these limitations. The proposal is implemented in the PiCasso system, which utilises in-network caching and name based routing of ICN, combined with our HANET (HArdware and NETwork Resources) service deployment heuristic, to optimise the forwarding path of service delivery in a network zone. We analyse the data collected from the Guifi.net Sants network zone, to develop a smart heuristic for the service deployment in that zone. Through a real deployment in Guifi.net, we show that HANET improves the response time up to 53% and 28.7% for stateless and stateful services respectively. PiCasso achieves 43% traffic reduction on service delivery in our real deployment, compared to the traditional host-centric communication. The overall effect of our ICN platform is that most content and service delivery requests can be satisfied very close to the client device, many times just one hop away, decoupling QoS from intra-network traffic and origin server load.Peer ReviewedPostprint (author's final draft

Socio-economic aware data forwarding in mobile sensing networks and systems

The vision for smart sustainable cities is one whereby urban sensing is core to optimising city operation which in turn improves citizen contentment. Wireless Sensor Networks are envisioned to become pervasive form of data collection and analysis for smart cities but deployment of millions of inter-connected sensors in a city can be cost-prohibitive. Given the ubiquity and ever-increasing capabilities of sensor-rich mobile devices, Wireless Sensor Networks with Mobile Phones (WSN-MP) provide a highly flexible and ready-made wireless infrastructure for future smart cities. In a WSN-MP, mobile phones not only generate the sensing data but also relay the data using cellular communication or short range opportunistic communication. The largest challenge here is the efficient transmission of potentially huge volumes of sensor data over sometimes meagre or faulty communications networks in a cost-effective way. This thesis investigates distributed data forwarding schemes in three types of WSN-MP: WSN with mobile sinks (WSN-MS), WSN with mobile relays (WSN-HR) and Mobile Phone Sensing Systems (MPSS). For these dynamic WSN-MP, realistic models are established and distributed algorithms are developed for efficient network performance including data routing and forwarding, sensing rate control and and pricing. This thesis also considered realistic urban sensing issues such as economic incentivisation and demonstrates how social network and mobility awareness improves data transmission. Through simulations and real testbed experiments, it is shown that proposed algorithms perform better than state-of-the-art schemes.Open Acces