S. Ioannidis

2papers

2 Papers

NIJan 17, 2018
Packet Routing in 3D Nanonetworks: A Lightweight, Linear-path Scheme

A. Tsioliaridou, C. Liaskos, E. Dedu et al.

Packet routing in nanonetworks requires novel approaches, which can cope with the extreme limitations posed by the nano-scale. Highly lossy wireless channels, extremely limited hardware capabilities and non-unique node identifiers are among the restrictions. The present work offers an addressing and routing solution for static 3D nanonetworks that find applications in material monitoring and programmatic property tuning. The addressing process relies on virtual coordinates from multiple, alternative anchor point sets that act as \emph{viewports}. Each viewport offers different address granularity within the network space, and its selection is optimized by a packet sending node using a novel heuristic. Regarding routing, each node can deduce whether it is located on the linear segment connecting the sender to the recipient node. This deduction is made using integer calculations, node-local information and in a stateless manner, minimizing the computational and storage overhead of the proposed scheme. Most importantly, the nodes can regulate the width of the linear path, thus trading energy efficiency (redundant transmissions) for increased path diversity. This trait can enable future adaptive routing schemes. Extensive evaluation via simulations highlights the advantages of the novel scheme over related approaches.

LGJan 29, 2021
No-Regret Caching via Online Mirror Descent

T. Si Salem, G. Neglia, S. Ioannidis

We study an online caching problem in which requests can be served by a local cache to avoid retrieval costs from a remote server. The cache can update its state after a batch of requests and store an arbitrarily small fraction of each file. We study no-regret algorithms based on Online Mirror Descent (OMD) strategies. We show that bounds for the regret crucially depend on the diversity of the request process, provided by the diversity ratio R/h, where R is the size of the batch, and h is the maximum multiplicity of a request in a given batch. We characterize the optimality of OMD caching policies w.r.t. regret under different diversity regimes. We also prove that, when the cache must store the entire file, rather than a fraction, OMD strategies can be coupled with a randomized rounding scheme that preserves regret guarantees, even when update costs cannot be neglected. We provide a formal characterization of the rounding problem through optimal transport theory, and moreover we propose a computationally efficient randomized rounding scheme.