Brief Announcement: Implementing Byzantine Tolerant Distributed Ledger Objects

Comunicación presentada en DISC 2019 International Symposium on Distributed Computing (Budapest, Hungary, 14-18 October 2019

Tight arrival curve at the output of a work-conserving blind multiplexing serve

As a means of supporting quality of service guarantees, aggregate multiplexing has attracted a lot of attention in the networking community, since it requires less complexity than flow-based scheduling. However, contrary to what happens in the case of flow-based multiplexing, few results are available for aggregate-based multiplexing. In this paper, we consider a server multiplexer fed by several flows and analyze the impact caused by traffic aggregation on the flows at the output of the server. No restriction is imposed on the server multiplexer other than the fact that it must operate in a work- conserving fashion. We characterize the best arrival curves that constrain the number of bits that leave the server, in any time interval, for each individual flow. These curves can be used to obtain the delays suffered by packets in complex scenarios where multiplexers are interconnected, as well as to determine the maximum size of the buffers in the different servers. Previous results provide tight delay bounds for networks where servers are of the FIFO type. Here, we provide tight bounds for any work-conserving scheduling policy, so that our results can be applied to heterogeneous networks where the servers (routers) can use different work-conserving scheduling policies such as First-In First-Out (FIFO), Earliest Deadline First (EDF), Strict Priority (SP), Guaranteed Rate scheduling (GR), etc

Exact Resource Allocation for Fair Wireless Relay

In relay-enabled cellular networks, the intertwined nature of network agents calls for complex schemes to allocate wireless resources. Resources need to be distributed among mobile users while considering how relay resources are allocated, and constrained by the traffic rate achievable by base stations and over backhaul links. In this work, we derive a resource allocation scheme that achieves max-min fairness across mobile users. Furthermore, the optimal allocation is found with linear complexity with respect to the number of mobile users and relays

Resource location based on precomputed partial random walks in dynamic networks

The problem of finding a resource residing in a network node (the \emph{resource location problem}) is a challenge in complex networks due to aspects as network size, unknown network topology, and network dynamics. The problem is especially difficult if no requirements on the resource placement strategy or the network structure are to be imposed, assuming of course that keeping centralized resource information is not feasible or appropriate. Under these conditions, random algorithms are useful to search the network. A possible strategy for static networks, proposed in previous work, uses short random walks precomputed at each network node as partial walks to construct longer random walks with associated resource information. In this work, we adapt the previous mechanisms to dynamic networks, where resource instances may appear in, and disappear from, network nodes, and the nodes themselves may leave and join the network, resembling realistic scenarios. We analyze the resulting resource location mechanisms, providing expressions that accurately predict average search lengths, which are validated using simulation experiments. Reduction of average search lengths compared to simple random walk searches are found to be very large, even in the face of high network volatility. We also study the cost of the mechanisms, focusing on the overhead implied by the periodic recomputation of partial walks to refresh the information on resources, concluding that the proposed mechanisms behave efficiently and robustly in dynamic networks.Comment: 39 pages, 25 figure

Coverage Optimization with a Dynamic Network of Drone Relays

The integration of aerial base stations carried by drones in cellular networks offers promising opportunities to enhance the connectivity enjoyed by ground users. In this paper, we propose an optimization framework for the 3-D placement and repositioning of a fleet of drones with a realistic inter-drone interference model and drone connectivity constraints. We show how to maximize network coverage by means of an extremal-optimization algorithm. The design of our algorithm is based on a mixed-integer non-convex program formulation for a coverage problem that is NP-Complete, as we prove in the paper. We not only optimize drone positions in a 3-D space in polynomial time, but also assign flight routes solving an assignment problem and using a strong geometrical tool, namely Bézier curves, which are extremely useful for non-uniform and realistic topologies. Specifically, we propose to fly drones following Bézier curves to seek the chance of approaching to clusters of ground users. This enhances coverage over time while users and drones move. We assess the performance of our proposal for synthetic scenarios as well as realistic maps extracted from the topology of a capital city. We demonstrate that our framework is near-optimal and using Bézier curves increases coverage up to 47 percent while drones move

Fair Cellular Throughput Optimization with the Aid of Coordinated Drones

Comunicación presentada en IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (Paris, 29 April-2 May 2019)The interest on flexible air-to-ground channels from aerial base stations to enhance users access by seeking good line-of-sight connectivity from the air has increased in the past years. In this paper, we propose a deployable analytical framework for the 3-D placement of a fleet of coordinated drone relay stations to optimize network capacity according to α-fairness metrics. We formulate a mixed-integer non-convex program, which results to be intractable. Therefore, we design a near-optimal heuristic that can solve the problem in real-time applications. We assess the performance of our proposal by simulation, using a realistic urban topology, and study pros and cons of using drone relay stations in both static and dynamic scenarios, when popular events gather masses of users in limited areas

Worst case burstiness increase due to FIFO multiplexing

We consider a FIFO multiplexer fed by flows that are individually constrained by arrival curves, and look for the best possible arrival curve for every output flow. This problem arises in scenarios where aggregate multiplexing is performed, such as differentiated services or front ends to optical switches. We obtain an exact result for a fluid model and for piecewise linear concave arrival curves, which are common in practice and correspond to combinations of leaky buckets

On the Feasible Scenarios at the Output of a FIFO Server

We consider the case of a FIFO multiplexer fed by flows that are individually constrained by piecewise linear concave arrival curves. We show that, contrary to what happens at the input, at the output not all valid scenarios in accordance with the worst case arrival curves can occur. This implies that taking an iterative approach to characterize the arrival curves at the output when flows pass throughout several FIFO nodes is suboptimal (in the sense that, although valid, they do not necessarily have to be the best arrival curves that can be found)