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Parking in major cities, particularly with dense traffic, directly effects the traffic flow and people's life. In this paper, we introduce a new smart parking system that is based on intelligent resource allocation, reservation, and pricing. The proposed system solves the current parking problems by offering guaranteed parking reservations with the lowest possible cost and searching time for drivers and the highest revenue and resource utilization for parking managers. New fair pricing policies are also proposed that can be implemented in practice. The new system is based on mathematical modeling using mixed-integer linear programming (MILP) with the objective of minimizing the total monetary cost for the drivers and maximizing the utilization of parking resources.Index Terms-Dynamic pricing, dynamic resource allocation, mixed integer linear programming (MILP), reservation, smart car parking.

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We present a new fabrication sequence for integrated-silicon microstructures designed and manufactured in a conventional complentary metal-oxide-semiconductor (CMOS) process. The sequence employs a post-CMOS deep silicon backside etch, which allows fabrication of high aspect ratio (25:1) and flat (greater than 10 mm radius of curvature) MEMS devices with integrated circuitry. A comb-drive resonator, a cantilever beam array and a -axis accelerometer were fabricated using this process sequence. Electrical isolation of single-crystal silicon was realized by using the undercut of the reactive ion etch (RIE) process. Measured out-of-plane curling across a 120m-wide 25-m-thick silicon released plate was 0.15 m, which is about ten times smaller than curl of the identical design as a thin-film CMOS microstructure. The -axis DRIE accelerometer structure is 0.4 mm by 0.5 mm in size and has a 25-m-thick single-crystal silicon proof mass. The measured noise floor is 1 mG/ Hz, limited by electronic noise. A vertical electrostatic spring "hardening" effect was theoretically predicted and experimentally verified.[687] IndexTerms-Complentary metal-oxide-semiconductor (CMOS) MEMS, deep reactive ion etch (DRIE), electrostatic spring, inertial sensors.

The transmission rate, delivery reliability and network lifetime are three fundamental but conflicting design objectives in energy-constrained wireless sensor networks. In this paper, we address the optimal rate-reliability-lifetime tradeoff with link capacity constraint, reliability constraint and energy constraint.By introducing the weight parameters, we combine the objectives at rate, reliability, and lifetime into a single objective to characterize the tradeoff among them. However, the optimization formulation of the rate-reliability-reliability tradeoff is neither separable nor convex. Through a series of transformations, a separable and convex problem is derived, and an efficient distributed Subgradient Dual Decomposition algorithm (SDD) is proposed. Numerical examples confirm its convergence. Also, numerical examples investigate the impact of weight parameters on the rate utility, reliability utility and network lifetime, which provide a guidance to properly set the value of weight parameters for a desired performance of WSNs according to the realistic application's requirements. Index TermsWireless sensor network, network utility maximization, rate allocation, reliability, network lifetime maximization . objectives in WSNs. There is an intrinsic tradeoff between them. However, all these works mentioned above didn't consider the intrinsic rate-reliability tradeoff problem. Recent work [10] has firstly addressed the rate-reliability tradeoff problem explicitly. Through the extended NUM framework, where the user utility depends on both transmission rate and delivery reliability, the optimal rate-reliability tradeoff can be controlled by adapting channel code rate in each link's physical-layer error correction codes. However, it did not take the energy constraint into consideration, which is one of the most important constraint in WSNs.Typically, sensor nodes are battery-powered, and battery replacement is impossible in many sensing applications. Energy is a scarce resource, and WSNs have a finite operational lifetime.Hence, network lifetime maximization has been a popular research direction in WSNs, for example, [6] has studied the network lifetime maximization problem that jointly considers the physical layer, MAC layer and routing layer.[11] design an near optimal joint routing-and-sleepscheduling strategy to maximize the network lifetime.[13] propose energy and cross-layer aware routing schemes for multichannel access WSNs that account for radio, MAC contention, and network constraints, aiming to maximize the network lifetime. [14] propose HYbrid Multi-hop routiNg (HYMN) algorithm, which is a hybrid of the flat multi-hop routing and hierarchical multihop routing, to adequately prolong the lifetime of severely resource-constrained sensor nodes.[12] address joint routing and link rate allocation under bandwidth and energy constraints to prolong network lifetime and to improve throughput. However, higher data rate leads to greater sensing and communication costs across WSNs, resulting in more energy consumpt...

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