Utku Günay Acer

Weak state routing for large scale dynamic networks

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 Θ(N3/2), where N is the number of nodes. Packets follow longer paths compared to prior protocols (OLSR , GLS-GPSR , ), but the average path length is asymptotically efficient and scales as O(√N). Despite longer paths, WSRs end-to-end packet delivery delay is much smaller due to the dramatic reduction in protocol overhead.

Timely Data Delivery in a Realistic Bus Network

WiFi-enabled buses and stops may form the backbone of a metropolitan delay-tolerant network, which 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 that 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 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: 1) minimizing the expected traversal time over our graph; 2) maximizing the delivery probability over an infinite time-horizon; and 3) 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 frequently fail (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 multicopy extension requires only ten copies to almost reach the performance of the costly flooding approach.

Timely data delivery in a realistic bus network

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 problem of how to route data from its source to its destination in order to maximize the delivery probability by a given deadline. We assume to know the bus schedule, but we take into account that randomness, due to road traffic conditions or passengers boarding and alighting, affects bus mobility. 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, minimizing the number of hops a packet can travel, and a recently-proposed heuristic based on bus frequencies. Our optimal algorithm outperforms all of them, but most of the times it essentially reduces to minimizing the expected traversal time. For values of deadlines close to the expected delivery time, the multi-copy extension requires only 10 copies to reach almost the performance of the costly flooding approach.

DMME: A distributed LTE mobility management entity

DMME is a distributed architecture that implements mobility management for next-generation cellular systems. It has been designed to serve as a scalable and cost-effective drop-in replacement for the Long Term Evolution (LTE) mobility management entity (MME). DMME is an example of a flexible control plane architecture that can be deployed incrementally across operator networks: processing locality is obtained by assigning control plane events to a local DMME replica and by allowing the transparent migration of control plane state across the different replicas as the users move. We evaluate the DMME scheme via analysis and simulation under several deployment scenarios, using mobility patterns drawn from both synthetic models and traces collected in a production network. Our analysis shows that DMME can achieve performances that are comparable with a centralized, server-based infrastructure in terms of system availability and signaling delay. Furthermore, we propose and evaluate a set of heuristics based on user behavior that specify the allocation policy of DMME instances over the available replicas. We also report preliminary performance figures from our DMME prototype implementation. Our results confirm that distributed architectures are a viable choice to reliably support high-throughput, latency-sensitive control plane functions such as cellular mobility management.

Human Data Interaction in IoT: The ownership aspect

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 individuals 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.

dMME: Virtualizing LTE mobility management

With the convergence between phone and data networks in LTE and 4G, cellular signaling traffic is increasingly carried over IP. Control plane functions, once performed by dedicated machinery, are evolving into large-scale network applications with strict requirements on delay, availability, and processing throughput as mandated by 3GPP standards. In this paper we present dMME, a distributed architecture that implements mobility management for next-generation cellular systems. dMME is a scalable and cost-effective drop-in replacement for the LTE mobility management entity (MME). We evaluate the dMME scheme via analysis and simulation under several deployment scenarios, using mobility patterns drawn from synthetic models and from traces collected in a production network. We also report preliminary performance figures by our dMME prototype implementation. Our results confirm that distributed architectures are a viable choice to reliably support high-throughput, latency-sensitive control plane functions.

Fast track article: Connectivity in time-graphs

Dynamic networks are characterized by topologies that vary with time and are represented by time-graphs. The notion of connectivity in time-graphs is fundamentally different from that in static graphs. End-to-end connectivity is achieved opportunistically by the store-carry-forward paradigm if the network is so sparse that source-destination pairs are usually not connected by complete paths. In static graphs, it is well known that the network connectivity is tied to the spectral gap of the underlying adjacency matrix of the topology: if the gap is large, the network is well connected. In this paper, a similar metric is investigated for time-graphs. To this end, a time-graph is represented by a 3-mode reachability tensor which indicates whether a node is reachable from another node in t steps. To evaluate connectivity, we consider the expected hitting time of a random walk, and the time it takes for epidemic routing to infect all vertices. Observations from an extensive set of simulations show that the correlation between the second singular value of the matrix obtained by unfolding the reachability tensor and these indicators is very significant.

DTN routing using explicit and probabilistic routing table states

AbstractRouting 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.

An Evaluation of Weak State Mechanism Design for Indirection in Dynamic Networks

State signaling and maintenance mechanisms play crucial roles in communication network protocols. State is used to facilitate indirections in protocols such as routing. Design approaches for traditional state signaling mechanisms have been categorized into soft and hard state. In both approaches, the state is deterministic. Hence, we call both as having strong state semantics, or more crisply, refer to them as strong state. If the state tracks entities with dynamic nature, strong state rapidly becomes invalidated and needs to be refreshed explicitly through control packets. In this paper, we evaluate the recently proposed weak state. Weak state is a generalization of soft state that is characterized by probabilistic semantics and local updates. It is interpreted as a probabilistic hint and not absolute truth. Weak state also contains the confidence in the state value, which is a measure of the probability that the state remains valid. The confidence or the state semantics is decayed locally without the need for explicit state update traffic traversing the network. The local updates also help the protocol use better estimates for the state value. We define two metrics, pure distortion and informed distortion, to evaluate the consistency of the weak state paradigm and compare it against strong state. Pure distortion measures the average gap between the actual value of the state and the value maintained at a remote node. On the other hand, the use of confidence increases the protocols ability to cope with even large pure distortion. The resulting effective distortion is captured by the informed distortion metric. Using mathematical analysis, we compare weak with strong state. Local updates reduce the pure distortion because the protocol uses the best estimate of state value. The informed distortion is also significantly less because the probabilistic confidence value hints the protocol if the state is invalid. The weak state mechanism can be used to build protocols (- eg: WSR [1]), which systematically interpret the state information. The state itself can be mostly updated locally, with less frequent explicit update messages over the network (i.e. leading to dramatic reductions in control traffic).

Exploring space syntax on entrepreneurial opportunities with Wi-Fi analytics

Industrial events and exhibitions play a powerful role in creating social relations amongst individuals and firms, enabling them to expand their social network so to acquire resources. However, often these events impose a spatial structure which impacts encounter opportunities. In this paper, we study the impact that the spatial configuration has on the formation of network relations. We designed, developed and deployed a Wi-Fi analytics solution comprising of wearable Wi-Fi badges and gateways in a large scale industrial exhibition event to study the spatio-temporal trajectories of the 2.5K+ attendees including two special groups: 34 investors and 27 entrepreneurs. Our results suggest that certain zones with designated functionalities play a key role in forming social ties across attendees and the different behavioural properties of investors and entrepreneurs can be explained through a spatial lens. Based on our findings we offer three concrete recommendations for future organisers of networking events.