Caching, Computing and Delivery in Wireless Networks Workshop (CCDWN)
Call for papers
With the ever-growing demand for connectivity in 6G networks, limited air interface resources, storage capabilities, network, and protocols, as well as throughput hungry and delay-sensitive applications challenge the effective processing of a large volume of data. The caching paradigm can enable the providers to provide faster downloads and cheaper services. Existing work in the field has demonstrated key savings through edge helpers, erasure coding, and distributed optimization techniques, and shed light on the fundamental limits of bandwidth and storage requirements. To satisfy the QoS requirements of emerging applications, the focus of the 7th Caching, Computing and Delivery in Wireless Networks Workshop (CCDWN) (previously known as Content Caching and Delivery in Wireless Networks) is to bring together techniques from optimization, information theory, and networking to enable personalized, intelligent, scalable, and secure caching at the edge and meet the stringent requirements in 6G networks. We believe that the high-quality contributions from the researchers in the field will advance the understanding of performance limits, closing the gap between theory and practice.
Topics of interests include but not limited to
Cache protocols, distributed and adaptive algorithms, effective relaxation and rounding techniques forplacement to provide optimality guarantees
Joint optimization of caching, routing, rate, power, congestion, delay for meeting throughput-latencyrequirements, providing guarantees and resilience to failures
Fairness and privacy in caching
Distributed reinforcement learning for caching
Caching for networking, caching in HetNets, spatial and temporal caching, content updates incache-aided networks, load balancing with asymmetric upload and download bandwidth, accounting forbackhaul cost and bottlenecks
Information-centric networking, named data networking
Caching for computation, coding for computation
Information theoretic limits and throughput scaling laws and the role of feedback