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In traditional machine learning, the central server first collects the data owners' private data together and then trains the model. However, people's concerns about data privacy protection are dramatically increasing. The emerging paradigm…
Crowdsourced mobile video streaming enables nearby mobile video users to aggregate network resources to improve their video streaming performances. However, users are often selfish and may not be willing to cooperate without proper…
The resource allocation problem of optimal assignment of the clients to the available access points in 60 GHz millimeterWave wireless access networks is investigated. The problem is posed as a multiassignment optimisation problem. The…
Cloud containers represent a new, light-weight alternative to virtual machines in cloud computing. A user job may be described by a container graph that specifies the resource profile of each container and container dependence relations.…
The rapid growth of Internet of Things (IoT) ecosystems has intensified the challenge of efficiently allocating heterogeneous resources in highly dynamic, distributed environments. Conventional centralized mechanisms and single-objective…
Many spectrum auction mechanisms have been proposed for spectrum allocation problem, and unfortunately, few of them protect the bid privacy of bidders and achieve good social efficiency. In this paper, we propose PPS, a Privacy Preserving…
With the recent growth in the size of cloud computing business, handling the interactions between customers and cloud providers has become more challenging. Auction theory has been proposed to model these interactions due to its simplicity…
Cooperative transmission can greatly improve communication system performance by taking advantage of the broadcast nature of wireless channels. Most previous work on resource allocation for cooperation transmission is based on centralized…
The cell-free architecture represents a significant advancement in network design, where each User Equipment (UE) is served by a group of distributed Access Points (APs), aimed at delivering uniformly high data rates to UEs across all…
Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D),…
By sharing resources among different cloud providers, the paradigm of federated clouds exploits temporal availability of resources and geographical diversity of operational costs for efficient job service. While interoperability issues…
Auction has been used to allocate resources or tasks to processes, machines or other autonomous entities in distributed systems. When different bidders have different demands and valuations on different types of resources or tasks, the…
The growing demand in mobile Internet access calls for high capacity and energy efficient cellular access with better cell coverage. The in-band relaying solution, proposed in LTE-Advanced, improves coverage without requiring additional…
In cloud investment markets, consumers are looking for the lowest cost and a desirable fairness while providers are looking for strategies to achieve the highest possible profit and return. Most existing models for auction-based resource…
Situations where a group of agents come together to jointly buy a resource that they individually cannot afford to buy are commonly observed in markets. For example in the US market for radio spectrum, a recent proposal invited small firms…
A novel distributed energy allocation mechanism for Distribution System Operator (DSO) market through a bi-level iterative auction is proposed. With the locational marginal price at the substation node known, the DSO runs an upper level…
We consider a double-auction mechanism, which was recently proposed in the context of rate allocation in mobile data-offloading markets. Network operators (users) derive benefit from offloading their traffic to third party WiFi or femtocell…
Multi-Access edge computing (MEC) is an emerging paradigm where users offload computationally intensive jobs to the Access Point (AP). Given that the AP's resources are shared by selfish users, pricing is a useful tool for incentivising…
In recent years, mobile clients' computing ability and storage capacity have greatly improved, efficiently dealing with some applications locally. Federated learning is a promising distributed machine learning solution that uses local…
We develop two distributed downlink resource allocation algorithms for user-centric, cell-free, spatially-distributed, multiple-input multiple-output (MIMO) networks. In such networks, each user is served by a subset of nearby transmitters…