Forwarding decisions in routing protocols rely on information about the destination nodes provided by routing table states. When paths to a destination change, corresponding states become invalid and need to be refreshed with control messages for resilient routing. In large and highly dynamic networks, this overhead can crowd out the capacity for data traffic. For such networks, we propose the concept of weak state, which is interpreted as a probabilistic hint, not as absolute truth. Weak state can remain valid without explicit messages by systematically reducing the confidence in its accuracy. Weak State Routing (WSR) is a novel routing protocol that uses weak state along with random directional walks for forwarding packets. When a packet reaches a node that contains a weak state about the destination with higher confidence than that held by the packet, the walk direction is biased. The packet reaches the destination via a sequence of directional walks, punctuated by biasing decisions. WSR also uses random directional walks for disseminating routing state and provides mechanisms for aggregating weak state. Our simulation results show that WSR offers a very high packet delivery ratio ( 98%). Control traffic overhead scales as O(N), and the state complexity is 2(N 3=2 ), where N is the number of nodes. Packets follow longer paths compared to prior protocols (OLSR [2], GLS-GPSR [3], [4]), but the average path length is asymptotically efficient and scales as O p N . Despite longer paths, WSR's end-to-end packet delivery delay is much smaller due to the dramatic reduction in protocol overhead. Index Terms-Dynamic networks, unstructured routing, weak state.

Abstract-As Internet of Things (IoT) becomes a growing reality, more ubiquitous devices are embedded in our daily lives, serving us in a broad range of purposes in everyday life from: personal healthcare to home automation to tailored smart city services. These devices primarily collect data that is about or produced by people, be it street noise level of a neighbourhood, or the energy footprint of an individual's home or her location and other situational context. As this unprecedented amount of data is collected, we are challenged with one fundamental research question: who owns this data and who should have access to it? Specifically, the emergent of the Human Data Interaction (HDI) topic which aims to put the human at the centre of the data driven industry, calls attention to the IoT community to address the data ownership aspect more carefully. In this note, we offer a reflection on the challenges that IoT faces in regards to the data ownership in HDI and advocate the roles that both ordinary people and industries must play to best answer those challenges in shaping the IoT landscape.

WiFi-enabled buses and stops may form the backbone of a metropolitan delay tolerant network, that exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real time information. This paper studies the routing problem in such a network. Assuming the bus schedule is known, we maximize the delivery probability by a given deadline for each packet. Our approach takes the randomness into account, which stems from road traffic conditions, passengers boarding and alighting, and other factors that affect the bus mobility. In this sense, this paper is one of the first to tackle quasi-deterministic mobility scenarios. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: minimizing the expected traversal time over our graph, maximizing the delivery probability over an infinite time-horizon, and a recently proposed heuristic based on bus frequencies. We show that our optimal algorithm shows the best performance, but it essentially reduces to minimizing the expected traversal time. When transmissions fail frequently (more than half of the times), the algorithm behaves similarly to a heuristic that maximizes the delivery probability over an infinite time-horizon. For reliable transmissions and values of deadlines close to the expected delivery time, the multi-copy extension requires only 10 copies to almost reach the performance of the costly flooding approach. I. INTRODUCTION We consider an opportunistic data network formed by (some) buses and bus stops in a town equipped with wireless devices, e.g. based on WiFi technologies, like in DieselNet [1]. Most of the stops act as disconnected relay nodes (the throwboxes in [2]), and a few of them are also connected to the Internet. Data are delivered across the town following the store-carry-forward network paradigm [3], based on multihop communication in which two nodes may exchange data

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Routing in communication networks involves the indirection from a persistent name (ID) to a locator. The locator specifies how packets are delivered to a destination with a particular ID. Such a mapping is provided by a routing table entry, i.e. state. In a DTN, it is hard to maintain routing state because intermittent connectivity prevents protocols from refreshing states when they become inaccurate. In prior work, per-destination state mostly corresponds to utilities, where a high utility value about a destination implies that the probability to encounter the destination for the node maintaining the state is high. This approach depends on a particular mobility pattern in which nodes that met frequently in the past are likely to encounter in the future. In this paper, we use the concept of weak state that does not rely on external messages to remain valid (Acer et al. in MobiCom '07: proceedings of the 13th annual ACM international conference on mobile computing and networking, pp 290-301, 2007). Our weak state realization provides probabilistic yet explicit information about where the destination is located. We build Weak State Routing protocol for Delay Tolerant Networks (WSR-D) that exploits the direction of node mobility in forwarding. It provides an osmosis mechanism to disseminate the state information to the network. With osmosis, a node has consistent information about a portion of the nodes that are located in regions relevant to its direction of mobility. Through simulations, we show that WSR-D achieves a higher delivery ratio with smaller average delay, and reduces the number of message transfers in comparison to Spray & Wait (Spyropoulos et al. in Proceedings of ACM SIGCOMM 2005 workshops: conference on computer communications, pp 252-259, 2005) and Spray & Focus (Spyropoulos et al. in IEEE/ACM Trans Netw, 16(1): 77-90, 2008), a stateless and a utility based protocol, respectively.

Routing in communication networks involves the indirection from a persistent name (or ID) to a locator and delivering packets based upon the locator. In a large-scale, highly dynamic network, the ID-to-locator mappings are both large in number, and change often. Traditional routing protocols require high overhead to keep these indirections up-to-date. In this paper, we propose Weak State Routing (WSR), a routing mechanism for large-scale highly dynamic networks. WSR's novelty is that it uses random directional walks biased occasionally by weak indirection state information in intermediate nodes. The indirection state information is weak, i.e. interpreted not as absolute truth, but as probabilistic hints. Nodes only have partial information about the region a destination node is likely to be. This method allows us to aggregate information about a number of remote locations in a geographic region. In other words, the state information maps a set-of-IDs to a geographical region. The intermediate nodes receiving the random walk use a method similar to longest-prefix-match in order to prioritize their mappings to decide how to bias and forward the random walk. WSR can also be viewed as an unstructured distributed hashing technique. WSR displays good rare-object recall with scalability properties similar to structured DHTs, albeit with more tolerance to dynamism and without constraining the degree distribution of the underlying network.Through simulations, we show that WSR offers a high packet delivery ratio, more than 98%. The control packet overhead incurred in the network scales as O(N ) for N -node networks. The number of mappings stored in the network appears to scale as Θ(N 3/2 ). We compare WSR with Dynamic Source Routing (DSR) and geographic forwarding (GPSR) combined with Grid Location Service (GLS). Our results indicate that WSR delivers more packets with less overhead at the cost of increased path length.