Understanding the energy demand of a city’s housing stock is an important focus for local and national administrations to identify strategies for reducing carbon emissions. Building energy simulation offers a promising approach to understand energy use and test plans to improve the efficiency of residential properties. As part of this, models of the urban stock must be created that accurately reflect its size, shape and composition. However, substantial effort is required in order to generate detailed urban scenes with the appropriate level of attribution suitable for spatially explicit simulation of large areas. Furthermore, the computational complexity of microsimulation of building energy necessitates consideration of approaches that reduce this processing overhead. We present a workflow to automatically generate 2.5D urban scenes for residential building energy simulation from UK mapping datasets. We describe modelling the geometry, the assignment of energy characteristics based upon a statistical model and adopt the CityGML EnergyADE schema which forms an important new and open standard for defining energy model information at the city-scale. We then demonstrate use of the resulting urban scenes for estimating heating demand using a spatially explicit building energy microsimulation tool, called CitySim+, and evaluate the effects of an off-the-shelf geometric simplification routine to reduce simulation computational complexity.

This paper proposes a novel fully distributed and collaborative k-anonymity protocol (LPAF) to protect users' location information and ensure better privacy while forwarding queries/replies to/from untrusted location-based service (LBS) over opportunistic mobile networks (OppMNets). We utilize a lightweight multihop Markov-based stochastic model for location prediction to guide queries toward the LBS's location and to reduce required resources in terms of retransmission overheads. We develop a formal analytical model and present theoretical analysis and simulation of the proposed protocol performance. We further validate our results by performing extensive simulation experiments over a pseudorealistic city map using map-based mobility models and using real-world data trace to compare LPAF to existing location privacy and benchmark protocols. We show that LPAF manages to keep higher privacy levels in terms of k-anonymity and quality of service in terms of success ratio and delay, as compared with other protocols, while maintaining lower overheads. Simulation results show that LPAF achieves up to an 11% improvement in success ratio for pseudorealistic scenarios, whereas real-world data trace experiments show up to a 24% improvement with a slight increase in the average delay.

This paper is concerned with fully distributed reputation-based mechanisms that improve security in MANETS. We introduce a number of optimisations to the current reputation schemes used in MANETs such as selective deviation tests and adaptive expiration timer that aim to deal with congestion and quick reputation convergence. We propose to use two different centrality measures for evaluation of the individual trust claims and resolving the aggregated ones. We design and build our prototype over AODV and test it in NS-2 in the presence of variable active blackhole attacks in highly mobile and sparse networks. Our results show that we achieve increased throughput while delay and jitter decrease and converge to AODV.

Location-tracking is a major privacy problem, especially with high penetration of smart-phones and GPS-enabled devices around the world. In this paper, we propose a Hybrid and Social-aware Location-Privacy in Opportunistic mobile social networks (HSLPO), a collaborative and distributed obfuscation protocol that offers location-privacy k-anonymity. HSLPO discovers the users' own social network and use it to obfuscate requests and hide the original sender's location from the Location based service (LBS) while minimizing the overhead needed to perform obfuscation. We performed extensive simulations over a map-based pseudo realistic environment to compare HSLPO to exiting protocols. Results show that HSLPO can reach higher location-privacy levels and quality of service, in term of success ratio, than other protocols while maintaining low overheads.