In this paper, we propose a two-layered parking lot management system for charging scheduling of electric vehicles (EVs) considering a realistic vehicular mobility pattern. EVs are categorized in two groups based on their mobility patterns: Regular EVs and Irregular EVs. We use the data from an vehicular mobility trace collected from the Canton of Zurich for the regular EVs and a probabilistic pattern built on top of this Zurich trace aiming at modeling the behavior of irregular EVs. To the extend of our knowledge, this is the first EV charging scheduling study in the literature that utilizes a big-scale realistic vehicular mobility trace. The performance of the proposed system is compared with well-known routine unaware scheduling mechanisms (e.g., First Come First Serve) with regard to maximizing the parking lot revenue. Our results show that, our proposed system outperforms well-known routine unaware scheduling mechanisms and it is evident that real environments would benefit from using such parking lot management systems in Smart Cities.

Interoperability is essential for the commercial adoption of wireless sensor networks. However, existing sensor network architectures have been developed in isolation and thus interoperability has not been a concern. Recently, IP has been proposed as a solution to the interoperability problem of low-power and lossy networks (LLNs), considering its open and standards-based architecture at the network, transport, and application layers. We present two complete and interoperable implementations of the IPv6 protocol stack for LLNs, one for Contiki and one for TinyOS, and show that the cost of interoperability is low: their performance and overhead is on par with state-of-the-art protocol stacks custom built for the two platforms. At the same time, extensive testbed results show that the ensemble performance of a mixed network with nodes running the two interoperable stacks depends heavily on implementation decisions and parameters set at multiple protocol layers. In turn, these results argue that the current industry practice of interoperability testing does not cover the crucial topic of the performance and motivate the need for generic techniques that quantify the performance of such networks and configure their run-time behavior.

Interoperability is key to widespread adoption of sensor network technology, but interoperable systems have traditionally been difficult to develop and test. We demonstrate an interoperable system development and performance diagnosis environment in which different systems, different software, and different hardware can be simulated in a single network configuration. This allows both development, verification, and performance diagnosis of interoperable systems. Estimating the performance is important since even when systems interoperate, the performance can be sub-optimal, as shown in our companion paper that has been conditionally accepted for SenSys 2011.

Path computation elements (PCE's) are used to compute end-to-end paths across multiple areas. Multiple PCE's may be dedicated to each area to provide sufficient path computation capacity and redundancy. An open problem is to which PCE to send the path computation request. This problem may be a non trivial problem if PCE's have uneven processing capacities. This paper presents a queueing model based on product form to estimate the latencies in path computation while accounting for the arrival rate of path computation requests. The model is used to find the PCE selection policy to minimize the overall expected latencies in path computation. Simulation studies demonstrate that the use of the simplistic product form approach yields reasonable approximations that are within up to 15% of the simulation results at practical offered loads.

In this paper, a quantitative study of the benefits and shortcomings of IP and MPLS traffic engineering techniques under realistic traffic variation scenarios is presented. While both techniques can achieve similar degree of optimization under steady state conditions, our simulation results show the impact on each when realistic traffic variations are induced in the network. A detailed simulator has been developed to facilitate the study, and several new metrics of interest are analyzed to present a novel point of view.

MPLS Fast Reroute advocates local protection mechanisms to rapidly reroute traffic onto pre-computed and signaled bypass tunnels. When the network is subject to multiple element failures, it becomes challenging to handle all the possible failure scenarios, for they are more disruptive and may require many more bypass tunnels to be dealt with. The objective of this paper is to adapt the MPLS local recovery schemes to deal with multi-failure scenarios, while retaining as much as possible the simplicity and the fast failure detection feature of current (single failure) local recovery mechanisms. This objective is achieved by optimally grouping failure patterns into clusters and minimizing the overall additional network resources - i.e., bypass tunnels and bidirectional forwarding detection sessions - while yielding full recovery from such failure patterns.

MPLS-TE (traffic engineering) fast reroute proposes a local protection mechanism to reroute protected TE LSPs (label switched paths) quickly onto precomputed and signaled bypass tunnels. The paper explores the case of multiple network element failure scenarios. The undesired complexity inherent in the multiple failure scenario originates from the fact that those failure scenarios are more disruptive, and may require multiple bypass tunnels to cope with them. The paper adapts the MPLS local recovery schemes to multi-failure scenarios, while controlling the number of bypass tunnels that are required. This is achieved by mapping multi-failure scenarios onto probable failure patterns (PFPs). PFPs are characterized by their probability (or frequency) of occurrence during the network lifetime. A number of bypass tunnels is then computed to cope effectively with the PFPs according to their frequency or probability of occurrence. It is shown that by properly choosing how the PFPs are grouped, and how the corresponding bypass tunnels are computed, it is possible to trade the required number of bypass tunnels for their average length and outage probability, i.e., the probability that the local recovery scheme cannot cope with the occurrence of a multi-failure pattern.