QoS evaluation of bandwidth schedulersin IPTV networks offered SRD fluidvideo traffic: a simulation study

IPTV is now offered by several operators in Europe, US and Asia using broadcast video over private IP networks that are isolated from Internet. IPTV services rely ontransmission of live (real-time) video and/or stored video. Video on Demand (VoD)and Time-shifted TV are implemented by IP unicast and Broadcast TV (BTV) and Near video on demand are implemented by IP multicast. IPTV services require QoS guarantees and can tolerate no more than 10-6 packet loss probability, 200 ms delay, and 50 ms jitter. Low delay is essential for satisfactory trick mode performance(pause, resume,fast forward) for VoD, and fast channel change time for BTV. Internet Traffic Engineering (TE) is defined in RFC 3272 and involves both capacity management and traffic management. Capacity management includes capacityplanning, routing control, and resource management. Traffic management includes (1)nodal traffic control functions such as traffic conditioning, queue management, scheduling, and (2) other functions that regulate traffic flow through the network orthat arbitrate access to network resources. An IPTV network architecture includes multiple networks (core network, metronetwork, access network and home network) that connects devices (super head-end, video hub office, video serving office, home gateway, set-top box). Each IP router in the core and metro networks implements some queueing and packet scheduling mechanism at the output link controller. Popular schedulers in IP networks include Priority Queueing (PQ), Class-Based Weighted Fair Queueing (CBWFQ), and Low Latency Queueing (LLQ) which combines PQ and CBWFQ.The thesis analyzes several Packet Scheduling algorithms that can optimize the tradeoff between system capacity and end user performance for the traffic classes. Before in the simulator FIFO,PQ,GPS queueing methods were implemented inside. This thesis aims to implement the LLQ scheduler inside the simulator and to evaluate the performance of these packet schedulers. The simulator is provided by ErnstNordström and Simulator was built in Visual C++ 2008 environmentand tested and analyzed in MatLab 7.0 under windows VISTA.

Skatte- och sysselsättningseffekter till följd av ett större idrottsevenemang : Förväntade effekter på regionens näringsliv till följd av ett kommande Skid VM i Falun 2015

Syfte: Att mäta turisternas konsumtion i samband med ett större idrottsevenemang samt att beräkna skatte- och sysselsättningseffekter till följd av denna under Skid-VM i Falun år 2015. Metod: Turisternas konsumtion har i denna studie mätts genom att ett urval av besökarna på Skidspelen 2013 fört dagbok över sin konsumtion. Vi har även använt sekundärdata i form av en konsumtionsundersökning som är genomförd under Svenska Skidspelen 2012 samt uppgifter från en rapport författad av HUI Research AB. Slutsats: Tre olika scenarion har använts för att beräkna skatte och sysselsättningseffekter. Ett lågt scenario där vi räknar med 140 000 sålda endagsbiljetter vilket är samma antal som Skid- VM i Falun 1993. Ett medelhögt där vi räknar med 200 000 sålda endagsbiljetter vilket är vad arrangören förväntar sig samt slutligen ett högt scenario med 270 000 sålda endagsbiljetter vilket är vad som såldes under Skid-VM i Oslo 2011. Beroende på valt scenario kommer turisternas totala konsumtion i regionen att uppgå till mellan 147 och 197 miljoner kronor. Denna omsättningsökning uppskattas leda till att mellan 85 och 111 arbetstillfällen skapas i regionen på kort sikt. Summan av samtliga skatter och avgifter uppgår till mellan 27 och 36 miljoner kronor.

The impact of big-boxes on local retail : What happens when IKEA comes to town?

The development of large discount retailers, or big-boxes as they are sometimes referred to, are often subject to heated debate and their entry on a market is greeted with either great enthusiasm or dread. For instance, the world’s largest retailer Wal-Mart (Forbes 2014) has a number of anti- and pro-groups dedicated to its being and the event of a Wal-Mart entry tends to be met with protests and campaigns (Decamme 2013) but also welcomed by, for instance, consumers (Davis & DeBonis 2013). Also in Sweden, the entry of a big box is a hot topic and before IKEA’s opening i Borlänge 2013, the first in Sweden in more than five years, great expectations were mixed with worry (Västerbottens-Kuriren 2011).The presence of large scale discount retailers is not, however, a novel phenomenon but a part of a long-term change in retailing that has taken place globally over the past couple of decades (Taylor & Smalling, 2005). As noted by Dawson (2006), the trend in Europe has over the past few decades gone towards an increasing concentration of large firms along with a decrease of smaller firms.This trend is also detectable in the Swedish retail industry. Over the past decade, the retailing industry in Sweden has increased by around 190 Billion SEK, and its share of GDP has risen from 2,7% to 2,9%, while the number of employees have increased from 200 000 to 250 000 (HUI 2013). This growth, however, has not been distributed evenly but rather it has been oriented mainly towards out-of-town retail clusters. Parallel to this development, the number of large retailers has risen at the expense of market shares of smaller independent firms (Rämme et al 2010). Thereby, the presence of large scale retailers is simply part of a changing retail landscape.The effects of this development, where large scale retailing agents relocate shopping to out-of-town shopping areas, have been heavily debated. On the one hand, the big-boxes are accused of displacing independent small retail businesses in the city-centers and the residential areas, resulting in, to some extent, reduced employment opportunities and less availability for the consumers - especially the elderly (Ljungberg et al 2006). In addition, as access to shopping now tends to require some sort of a motorized vehicle, environmental aspects to the discussion have emerged. Ultimately these types of concerns have resulted in calls for regulations against this development (Olsson 2010). On the other hand, the proponents of the new shopping landscape argue that this evolution implies productivity gains, the benefits of lower prices and an increased variety of products (Maican & Orth 2012). Moreover it is argued that it leads to, for instance, better services (such as longer opening hours) and a creative destruction transformation pressure on retailers, which brings about a renewal of city-centerIIretail and services, increasing their attractivity (Bergström 2010). The belief in benefits of a big box entry can be exemplified by the attractivity of IKEA, and the fact that municipalities are prepared to commit to expenses amounting up to hundreds of millions in order to attract the entry of this big-box. Borlänge municipality, for instance, agreed to expenses of about 350 million SEK in order to secure the entry of IKEA, which opened in 2013 (Blomgren 2009).Against this backdrop, the overall effects of large discount retailers become important: Are the economic benefits enough to warrant subsidies or are there, on the contrary, some very compelling grounds for regulations against these types of establishments? In other words; how is overall retail in a region where a store like IKEA enters affected? And how are local retail firms affected?In order to answer these questions, the purpose of this thesis is to study how entry of a big-box retailer affects the entry region. The object of this study is IKEA - one of the world’s largest retailers, with 345 stores, active in over 40 countries and with profits of about 3.3 billion (IKEA 2013; IKEA 2014). By studying the effects of IKEA-entry, both on an aggregated level and on firm level, this thesis intends to find indications of how large discount retail establishments in general can be expected to affect the economic development both in a region overall, but also on the local firm level, something which is of interest to both policymakers as well as the retailing industry in general.The first paper examines the effects of IKEA on retail revenues and employment in the municipalities that IKEA chose to enter between 2000 and 2011; Gothenburg, Haparanda, Kalmar and Karlstad. By means of a matching method we first identify non-entry municipalities that have a similar probability of IKEA entry as the true entry municipalities. Then, using these non-entry municipalities as a control group, the causal effects of IKEA entry can be estimated using a treatment-control approach. We also extend the analysis to examine the spatial impact of IKEA by estimating the effects on retail in neighboring municipalities. It is found that a new IKEA store increases revenues in durable goods trade with 20% in the entry municipality and the number of employees with 17%. Only small, and in most cases statistically insignificant, negative effects were found in neighboring municipalities.It appears that there is a positive net effect on durables retail sales and employment in the entry municipality. However, the analysis is based on data on an aggregated municipality level and thereby it remains unclear if and how the effects vary within the entry municipalities. In addition, the data used in the first study includes the sales and employment of IKEA itself, which could account for the majority of the increases in employment and retail. Thereby the potential spillover effects on incumbent retailers in the entry municipalities cannot be discerned in the first study.IIITo examine effects of IKEA entry on incumbent retail firms, the second paper in this thesis analyses how IKEA entry affects the revenues and employment of local retail firms in three municipalities; Haparanda, Kalmar and Karlstad, which experienced entry by IKEA between 2000 and 2010. In this second study, we exclude Gothenburg due to the fact that big-box entry appears to have weaker effects in metropolitan areas (as indicated by Artz & Stone 2006). By excluding Gothenburg we aim to reduce the geographical heterogeneity in our study. We obtain control municipalities that are as similar as possible to the three entry municipalities using the same method as in the previous study, but including a slightly different set of variables in the selection equation. Using similar retail firms in the control municipalities as our comparison group, we estimate the impact of IKEA entry on revenues and employment for retail firms located at varying distances from the IKEA entry site.The results generated in this study imply that entry by IKEA increases revenues in incumbent retail firms by, on average, 11% in the entry municipalities. In addition, we do not find any significant impact on retail revenues in the city centers of the entry municipalities. However, we do find that retail firms within 1 km of the IKEA experience increases in revenues of about 26%, which indicates large spillover effects in the area nearby the entry site. As expected, this impact decreases as we expand the buffer zone: firms located between 0-2 km experiences a 14% increase and firms in 2-5 km experiences an increase of 10%. We do not find any significant impacts on retail employment.

Arbetslöshet som en icke önskvärd konsekvens av socialbidrag : Resultat från en tidsserieanalys på befolkningsnivå i Sverige 1946–1990

Unemployment as an unintended consequence of social assistance recipiency: results from a time-series analysis of aggregated population data Does the frequency of unemployment have a tendency to increase the number of social assistance recipients, or does the relationship work the other way around? This article utilizes Swedish annual data on aggregated unemployment and means-tested social assistance recipiency in the period 1946–1990 and proposes a multiple time-series approach based on vector error-correction modelling to establish the direction of influence. First, we show that rates of unemployment and receipt of social assistance is co-integrated. Second, we demonstrate that adjustments to the long-run equilibrium are made through adjustments of the unemployment. This indicates that the level of unemployment reacts to changes in rates of social assistance recipiency rather than vice versa. It is also shown that lagged changes in the level of unemployment do not predict changes in rates of social assistance recipients in short-term. Together these findings demonstrate that the number of social assistance recipients does increase the number of unemployed in a period characterized by low unemployment and high employment.

How does data quality in a network affect heuristic solutions?

To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p). The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.