A native content discovery mechanism for the information-centric networks

Recent research has considered various approaches for discovering content in the cache-enabled nodes of an Autonomous System (AS) to reduce the costly inter-AS traffic. Such approaches include i) searching content opportunistically (on-path) along the default intra-AS path towards the content origin for limited gain, and ii) actively coordinate nodes when caching content for significantly higher gains, but also higher overhead. In this paper, we try to combine the merits of both worlds by using traditional opportunistic caching mechanisms enhanced with a lightweight content discovery approach. Particularly, a content retrieved through an inter-AS link is cached only once along the intra-AS delivery path to maximize network storage utilization, and ephemeral forwarding state to locate temporarily stored content is established opportunistically at each node along that path during the processing of Data packets. The ephemeral forwarding state either points to the arriving or the destination face of the Data packet depending on whether the content has already been cached along the path or not. The challenge in such an approach is to appropriately use and maintain the ephemeral forwarding state to minimize inter-AS content retrieval, while keeping retrieval latency and overhead at acceptable levels. We propose several forwarding strategies to use and manage ephemeral state and evaluate our mechanism using an ISP topology for various system parameters. Our results indicate that our opportunistic content discovery mechanism can achieve near-optimal performance and significantly reduce inter-AS traffic

A keyword-based ICN-IoT platform

Information-Centric Networking (ICN) has been proposed as a promising solution for the Internet of Things (IoT), due to its focus on naming data, rather than endpoints, which can greatly simplify applications. The hierarchical naming of the Named-Data Networking (NDN) architecture can be used to name groups of data values, for example, all temperature sensors in a building. However, the use of a single naming hierarchy for all kinds of different applications is inflexible. Moreover, IoT data are typically retrieved from multiple sources at the same time, allowing applications to aggregate similar information items, something not natively supported by NDN. To this end, in this paper we propose (a) locating IoT data using (unordered) keywords combined with NDN names and (b) processing multiple such items at the edge of the network with arbitrary functions. We describe and evaluate three different strategies for retrieving data and placing the calculations in the edge IoT network, thus combining connectivity, storage and computing

DEEM: Enabling microservices via DEvice edge markets

Native applications running over handheld devices have an irreplaceable role in users' daily activities. That said, recent studies show that users download on average zero new applications on monthly basis, which suggests that new apps can face discoverability issues. In this work, we aim for a web-based, download/installation-free access to native application features through microservices (μ Services)that are shared between user devices in a peer-to-peer (P2P)manner. Such a P2P approach is self-scalable and requires no investment for μ Service deployment, unlike mobile edge computing or Data Centre. We introduce DEEM, a DEvice Edge Market design that enables device-hosted μServices to end-users. In DEEM, μ Service-based markets act as rendezvous points between available μ Service instances and clients. DEEM ensures the i) assignment of instances to the users that value them the most, in terms of QoS gain, and ii) devices' income maximisation. Our evaluation on synthetic settings demonstrates DEEM's capability in exploiting the pool of device instances for improving the application QoS in terms of latency

ChainSoft: Collaborative software development using smart contracts

In recent years, more and more companies require dedicated software to increase the efficiency of their business. However, with rapidly changing technologies it is often inefficient to maintain a dedicated team of developers. On the other hand, outsourcing software development requires considerable effort and trust between involved parties to ensure the quality of the code and adequate payment. We present ChainSoft - a platform for outsourcing software development and automatic payments between parties that distrust each other, by means of blockchain technology. ChainSoft allows any developer to create software and submit software, includes automatic code verification and enforce users' proper behavior. We implement our system using Ethereum Smart Contracts and Github/Travis CI and present first evaluation proving its security and low usage cost

On-Demand Routing for Scalable Name-Based Forwarding

Information-centric Networking (ICN) is a future Internet architecture design, where application-level names are directly used to route interests to fetch a copy of the desired content/data from any location. Following the conventions of the Internet Protocol to store the pre-computed routing/forwarding state for all prefixes at the network nodes raises scalability concerns in ICN (where content name prefixes need to be stored), especially at the inter-domain level. Instead, we consider the other extreme; that is, On-Demand Routing (ODR) computation for content name prefixes as interests arrive. ODR makes use of domain-level, per-prefix routing instructions usable by all the forwarders in a domain, named Routing Information Objects (RIO). Forwarders discover and retrieve RIOs in a similar way as content and can be cached in a new data structure called Route Information Store (RIS). RIOs are handed to a routing strategy module to perform a routing decision before relaying the packets. We demonstrate through extensive simulations that ODR scales the storage of routing/forwarding information through caching and information discovery-two mechanisms inherent to the ICN design. We propose our design as an extension of the Named Data Networking (NDN) architecture and discuss all the proposed enhancements in detail

FogSpot: Spot Pricing for Application Provisioning in Edge/Fog Computing

An increasing number of Low Latency Applications (LLAs) in the entertainment, IoT, and automotive domains require response times that challenge the traditional application provisioning using distant Data Centres. Fog computing paradigm extends cloud computing at the edge and middle-tier locations of the network, providing response times an order of magnitude smaller than those that can be achieved by the current "client-to-cloud" network model. Here, we address the challenges of provisioning heavily stateful LLA in the setting where fog infrastructure consists of third-party computing resources, i.e., cloudlets, that comes in the form of "data centres in the box". We introduce FogSpot, a charging mechanism for on-path, on-demand, application provisioning. In FogSpot, cloudlets offer their resources in the form of Virtual Machines (VMs) via markets, collocated with the cloudlets, that interact with forwarded users' application requests for VMs in real time. FogSpot associates each cloudlet with a spot price based on current application requests. The proposed mechanism's design takes into account the characteristics of cloudlets' resources, such as their limited elasticity, and LLAs' attributes, like the expected QoS gain and engagement duration. Lastly, FogSpot guarantees end users' requests truthfulness while focusing in maximising either each cloudlet's revenue or resource utilisation

Shard scheduler: object placement and migration in sharded account-based blockchains

We propose Shard Scheduler, a system for object placement and migration in account-based sharded blockchains. Our system calculates optimal placement and decides on object migrations across shards. It supports complex multi-account transactions caused by smart contracts. Placement and migration decisions made by Shard Scheduler are fully deterministic, verifiable, and can be made part of the consensus protocol. Shard Scheduler reduces the number of costly cross-shard transactions, ensures balanced load distribution and maximizes the number of processed transactions for the blockchain as a whole. To this end, it leverages a novel incentive model motivating miners to maximize the global throughput of the entire blockchain rather than the throughput of a specific shard. In our simulations, Shard Scheduler can reduce the number of costly cross-shard transactions by half while ensuring equal load and increasing throughput more than 2 fold when using 60 shards. We also implement and evaluate Shard Scheduler on Chainspace, more than doubling its throughput and reducing user-perceived latency by 70% when using 10 shards

Data Availability Sampling in Ethereum: Analysis of P2P Networking Requirements

Despite their increasing popularity, blockchains still suffer from severe scalability limitations. Recently, Ethereum proposed a novel approach to block validation based on Data Availability Sampling (DAS), that has the potential to improve its transaction per second rate by more than two orders of magnitude. DAS should also significantly reduce per-transaction validation costs. At the same time, DAS introduces new communication patterns in the Ethereum peer-to-peer (P2P) network. These drastically increase the amount of exchanged data and impose stringent latency objectives. In this paper, we review the new requirements for P2P networking associated with DAS, discuss open challenges, and identify new research directions

Decentralised Edge-Computing and IoT through Distributed Trust

The emerging Internet of Things needs edge-computing - this is an established fact. In turn, edge computing needs infrastructure decentralisation. What is not necessarily established yet is that infrastructure decentralisation needs a distributed model of Internet governance and decentralised trust schemes. We discuss the features of a decentralised IoT and edge-computing ecosystem and list the components that need to be designed, as well the challenges that need to be addressed

Division of Baby Care in Heterosexual and Lesbian Parents: Expectations Versus Reality

ObjectiveWe examined the extent to which prenatal expectations matched postpartum reality, and the implications of expectancy violation for relationship quality at postpartum, among heterosexual and lesbian couples transitioning to parenthood.BackgroundDuring the transition to parenthood, soon‐to‐be parents form expectations about how their lives will change after their baby is born; however, these expectations may not match reality.MethodWe longitudinally examined (a) expectancy violation in division of baby care among 47 heterosexual and lesbian couples transitioning to first‐time parenthood (total N = 94 participants) and (b) the associations between expectancy violation and relationship quality at 3 and 10‐months postpartum.ResultsWe found that expectations matched reality for lesbian couples, but not for heterosexual couples: Heterosexual mothers did more baby care than they expected, and fathers did less. Heterosexual birth mothers were less satisfied when they did more baby care than they expected, whereas fathers were both less satisfied and less invested in their relationship when they did more baby care than they expected. In contrast, for lesbian birth mothers and nonbirth mothers, doing more baby care than anticipated was not associated with postpartum relationship quality. These results remained even after controlling for prenatal relationship quality and timing of postpartum assessments.ConclusionThe extent to which prenatal expectations match postpartum reality, and the outcomes of expectancy violation, may be different for heterosexual and lesbian couples.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/167038/1/jomf12729.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167038/2/jomf12729_am.pd