Bandwidth Constrained Multi-interface Networks

International audienceIn heterogeneous networks, devices can communicate by means of multiple wired or wireless interfaces. By switching among interfaces or by combining the available interfaces, each device might establish several connections. A connection is established when the devices at its endpoints share at least one active interface. Each interface is assumed to require an activation cost, and provides a communication bandwidth. In this paper, we consider the problem of activating the cheapest set of interfaces among a network G = (V,E) in order to guarantee a minimum bandwidth B of communication between two specified nodes. Nodes V represent the devices, edges E represent the connections that can be established. In practical cases, a bounded number k of different interfaces among all the devices can be considered. Despite this assumption, the problem turns out to be NP-hard even for small values of k and Δ, where Δ is the maximum degree of the network. In particular, the problem is NP-hard for any fixed k ≥ 2 and Δ ≥ 3, while it is polynomially solvable when k = 1, or Δ ≤ 2 and k = O(1). Moreover, we show that the problem is not approximable within ηlogB or Ω(loglog|V|) for any fixed k ≥ 3, Δ ≥ 3, and for a certain constant η, unless P=NP. We then provide an approximation algorithm with ratio guarantee of b max , where b max is the maximum communication bandwidth allowed among all the available interfaces. Finally, we focus on particular cases by providing complexity results and polynomial algorithms for Δ ≤ 2

Min-Max Coverage in Multi-interface Networks

International audienceWe consider devices equipped with multiple wired or wireless interfaces. By switching among interfaces or by combining the available interfaces, each device might establish several connections. A connection is established when the devices at its endpoints share at least one active interface. Each interface is assumed to require an activation cost. In this paper, we consider the problem of establishing the connections defined by a network G = (V,E) while keeping as low as possible the maximum cost set of active interfaces at the single nodes. Nodes V represent the devices, edges E represent the connections that must be established. We study the problem of minimizing the maximum cost set of active interfaces among the nodes of the network in order to cover all the edges. We prove that the problem is NP-hard for any fixed Δ ≥ 5 and k ≥ 16, with Δ being the maximum degree, and k being the number of different interfaces among the network. We also show that the problem cannot be approximated within Ω(ln Δ). We then provide a general approximation algorithm which guarantees a factor of O((1 + b)ln (Δ)), with b being a parameter depending on the topology of the input graph. Interestingly, b can be bounded by a constant for many graph classes. Other approximation and exact algorithms for special cases are presented

Distributed Energy-Saving Algorithms for Wireless Networks

The rapid growth of wireless networks has led to increasing interest in designing new algorithms that can efficiently reduce the energy consumption of routers and other devices. We present a new formulation of the Network Flow problem that takes into account the energy consumption of the data flows, and reduces the overall network energy expenditure. We introduce an energy model for wireless connections and analyse its validity with real measurements. Then we propose a convex optimization problem that establishes energy constraints on the links, and encourages energy savings that induce sparsity (shut-off of links). We propose several algorithms that can be computed in a distributed fashion for different types of capacity constraints. Finally we justify the sparsity of the solution by using the theory of proximal methods and present simulations for different scenarios. Our algorithms have application both in wired networks as well as in TDMA and 802.11 wireless networks

Decentralized Collective Learning for Self-managed Sharing Economies

The Internet of Things equips citizens with a phenomenal new means for online participation in sharing economies. When agents self-determine options from which they choose, for instance, their resource consumption and production, while these choices have a collective systemwide impact, optimal decision-making turns into a combinatorial optimization problem known as NP-hard. In such challenging computational problems, centrally managed (deep) learning systems often require personal data with implications on privacy and citizens’ autonomy. This article envisions an alternative unsupervised and decentralized collective learning approach that preserves privacy, autonomy, and participation of multi-agent systems self-organized into a hierarchical tree structure. Remote interactions orchestrate a highly efficient process for decentralized collective learning. This disruptive concept is realized by I-EPOS, the Iterative Economic Planning and Optimized Selections, accompanied by a paradigmatic software artifact. Strikingly, I-EPOS outperforms related algorithms that involve non-local brute-force operations or exchange full information. This article contributes new experimental findings about the influence of network topology and planning on learning efficiency as well as findings on techno-socio-economic tradeoffs and global optimality. Experimental evaluation with real-world data from energy and bike sharing pilots demonstrates the grand potential of collective learning to design ethically and socially responsible participatory sharing economies

Fast file transfers from IoT devices by using multiple interfaces

The Internet-of-Things (IoT) is a modern technological revolution that enables communication amongst a plethora of different devices. To date, about 30 billion devices have been connected to the internet and more than 75 billion devices are probably to be connected worldwide by 2025. These can range from small sensors and actuators to larger devices such as smartphones, drones or even buildings and interconnected cars. Devices are often mobile and battery powered thus their communication requires fast and energy efficient solutions. To this end, this paper studies the use of multi-interface communication for fast and energy efficient communication. In particular, we consider the basic operation of data transfer between smartphones in the form of files. This task can be performed for backup purposes, and hence it represents a useful and frequent operation that users perform. Our aim is to provide a new and easy means that optimises file transfers with respect to time and energy consumption. In particular, as smartphones are endowed with various connecting interfaces like Bluetooth, WiFi and 4G, we conduct experimental studies by varying different parameters in order to understand the best setting, including which interface is more appropriate to accomplish file transfer. To this respect, we also implemented an innovative and light app that allows the use of two or more interfaces concurrently. The experimental results show how the coupling of some interfaces might be effective in terms of time, while consuming a negligible amount of energy. Actually, such results become more and more interesting as the size of the file to be transferred grows. The best combination experienced is by making use of WiFi at 5 GHz concurrently with 4G, whereas WiFi at 2.4 GHz caused interference complications

Robust Controller for Delays and Packet Dropout Avoidance in Solar-Power Wireless Network

Solar Wireless Networked Control Systems (SWNCS) are a style of distributed control systems where sensors, actuators, and controllers are interconnected via a wireless communication network. This system setup has the benefit of low cost, flexibility, low weight, no wiring and simplicity of system diagnoses and maintenance. However, it also unavoidably calls some wireless network time delays and packet dropout into the design procedure. Solar lighting system offers a clean environment, therefore able to continue for a long period. SWNCS also offers multi Service infrastructure solution for both developed and undeveloped countries. The system provides wireless controller lighting, wireless communications network (WI-FI/WIMAX), CCTV surveillance, and wireless sensor for weather measurement which are all powered by solar energy