Smart Grid (SG) networks include an associated data network for the transmission and reception of control data related to the electric power supply service. A subset of this data network is the SG Neighborhood Area Network (SG NAN), whose objective is to interconnect the subscribers' homes with the supplier control center. The data flows transmitted through these SG NANs belong to different applications, giving rise to the need for different quality of service requirements. Additionally, other subscriber appliances could use this network to communicate over the Internet. To avoid network congestion, as well as to differentiate the quality of service (QoS) received by the different data flows, a congestion control mechanism with traffic differentiation capabilities is required. The main contribution of this work is the proposal of a new congestion control mechanism based on machine learning techniques to try to guarantee the different QoS requirements to the different data flows. A main problem when applying machine learning techniques is the need for datasets to be used in the training steps. In this sense, a second contribution of this article is the proposal of a method to generate such datasets by means of simulation techniques. The proposed mechanism is then evaluated in the context of a wireless SG NAN. The nodes of this network are the subscriber's smart meters, which in turn perform the function of concentrating the data traffic sent and received by the rest of the home appliances. Besides, different machine learning classification methods are taken into account. The evaluation carried out shows significant improvements in terms of network throughput, transit time, and quality of service differentiation. Finally, the computational cost of the algorithms used in this proposal has also been evaluated, using real low-cost IoT hardware platforms.
This paper presents an efficient and practical protocol to carry out micropayments, based on the use of anonymous mobile cash, that provides anonymity and unlinkability to customers. The mobile cash used in the protocol can be of different value and denomination. It is official after a bank signs it with a specific private key. The bank stores the relation between the mobile cash's value and its corresponding public key. The scheme prevents double spending and forgery attacks. A mobile device that supports java applications and Bluetooth technology is required. Through the use of pseudonym certificates customers can be authenticated using WTLS protocol without disclosing personal information. The protocol requires a low computational cost.
Online mobile payment systems based on mobile cash provide privacy to customers and are feasible for real point of sale, virtual point of sale, and person-to-person mobile commerce scenarios. The merchant does not perform complex operations and the bank verifies the validity of the mobile cash before the merchant delivers the product. The bank must store the mobile cash spent in a database to prevent a double spending attack. In this paper, we propose an efficient mobile cash scheme in which the customer attaches the expiration date and deposit date. This property reduces the size of the bank’s database and the customer must spend the mobile cash before expiry. Moreover, the customer attaches the merchant’s identity into the mobile cash in the deposit phase. The scheme requires low computational cost and is suitable for mobile devices
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